1"use strict";(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[4521],{32562:(e,i,t)=>{t.d(i,{r5:()=>n,sO:()=>a});let n=[{id:"openai",name:"OpenAI",description:"OpenAI, founded in 2015, is behind breakthrough AI tools like ChatGPT, DALL\xb7E, and Codex. Focused on making AI safe and useful, it's constantly pushing boundaries in research and innovation. From language models to image generators, OpenAI's projects are reshaping tech. Check out the latest updates, projects, and news to see how OpenAI is building the future.",website:"https://openai.com",apiDocumentation:"https://platform.openai.com/docs/api-reference",models:["gpt-4o","gpt-4o-mini","o3-mini","o1","gpt-4.5-preview","text-embedding-3-small"],founded:"2015",headquarters:"San Francisco, California, USA",ceo:"Sam Altman",employees:"375+",funding:"$11.3B+",valuation:"$80B+",specialties:["Large Language Models","Multimodal AI","AI Safety","Research"],keyProducts:["ChatGPT","DALL-E","Codex","GPT-4","Whisper"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Slack","Discord","Microsoft","Salesforce","Zapier"],useCases:["Content Generation","Code Development","Customer Support","Creative Writing","Data Analysis"],certifications:["SOC 2","GDPR Compliant","ISO 27001"],partnerships:["Microsoft","Salesforce","Stripe"],socialMedia:{twitter:"https://twitter.com/OpenAI",linkedin:"https://linkedin.com/company/openai",blog:"https://openai.com/blog"},contactInfo:{support:"https://help.openai.com",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"anthropic",name:"Anthropic",description:"Anthropic is an AI research company founded in 2021 by former OpenAI team members. Known for its Claude language models, Anthropic focuses on building safe, aligned AI systems. The team works on creating AI that's reliable, interpretable, and easy to steer. Stay informed with the latest updates, projects, and news as Anthropic continues shaping the future of responsible AI.",website:"https://www.anthropic.com",apiDocumentation:"https://docs.anthropic.com/claude/reference",models:["claude-3.5-sonnet","claude-3.5-haiku","claude-3.5-haiku-new","claude-3.7-sonnet","claude-3.5-sonnet-v2.0"],founded:"2021",headquarters:"San Francisco, California, USA",ceo:"Dario Amodei",employees:"500+",funding:"$7.3B+",valuation:"$18B+",specialties:["AI Safety","Constitutional AI","Large Language Models","Research"],keyProducts:["Claude","Claude Pro","Claude Enterprise","Anthropic Console"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Slack","Discord","Notion","Zapier"],useCases:["Content Creation","Research","Customer Support","Code Review","Data Analysis"],certifications:["SOC 2","GDPR Compliant"],partnerships:["Amazon","Google","Salesforce"],socialMedia:{twitter:"https://twitter.com/AnthropicAI",linkedin:"https://linkedin.com/company/anthropic-ai",blog:"https://www.anthropic.com/news"},contactInfo:{support:"https://support.anthropic.com",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"amazon",name:"Amazon",description:"Amazon started as an online bookstore in 1994 and quickly grew into one of the world's biggest tech companies. From e-commerce and AWS to Alexa and Prime Video, Amazon keeps expanding its reach. Its latest projects span cloud computing, AI, and logistics innovation. Stay updated on Amazon news, product launches, and tech breakthroughs shaping global commerce and customer experience.",website:"https://aws.amazon.com/bedrock",apiDocumentation:"https://docs.aws.amazon.com/bedrock",models:["amazon-nova-pro","amazon-titan-premier","nova-lite","nova-micro","titan-express","titan-lite"],founded:"1994",headquarters:"Seattle, Washington, USA",ceo:"Andy Jassy",employees:"1.5M+",funding:"Public Company",valuation:"$1.7T+",specialties:["Cloud Computing","E-commerce","AI/ML","Logistics","Entertainment"],keyProducts:["AWS","Amazon Bedrock","Alexa","Prime","Amazon.com"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["AWS Services","Lambda","S3","EC2","CloudFormation"],useCases:["Enterprise AI","Cloud Computing","E-commerce","Voice Assistants","Data Processing"],certifications:["SOC 2","ISO 27001","FedRAMP","HIPAA"],partnerships:["Anthropic","Meta","Stability AI"],socialMedia:{twitter:"https://twitter.com/awscloud",linkedin:"https://linkedin.com/company/amazon",blog:"https://aws.amazon.com/blogs/"},contactInfo:{support:"https://aws.amazon.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"google",name:"Google",description:"Google began in 1998 as a search engine and grew into a global tech giant. From Android and Chrome to Google Cloud and AI tools like Gemini, its innovations shape everyday life. With ongoing projects in AI, quantum computing, and sustainability, Google stays at the forefront of tech. Catch the latest Google news, updates, and launches across its vast ecosystem.",website:"https://ai.google.dev",apiDocumentation:"https://ai.google.dev/docs/gemini_api_overview",models:["gemini-2.0-flash","gemini-2.0-pro","gemini-2.0-flash-lite","gemma2-9b-it","gemini-2.5-pro","gemini-2.0-flash-exp-image-generation","gemma-3-4b","gemma-3-12b","gemma-3-27b"],founded:"1998",headquarters:"Mountain Vie
1w, California, USA",ceo:"Sundar Pichai",employees:"156,500+",funding:"Public Company",valuation:"$1.8T+",specialties:["Search","AI/ML","Cloud Computing","Mobile","Advertising"],keyProducts:["Google Search","Gemini","Google Cloud","Android","Chrome"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Google Cloud","Firebase","Vertex AI","BigQuery"],useCases:["Search","Content Generation","Code Development","Data Analysis","Mobile Apps"],certifications:["SOC 2","ISO 27001","FedRAMP","HIPAA"],partnerships:["OpenAI","Anthropic","Meta"],socialMedia:{twitter:"https://twitter.com/GoogleAI",linkedin:"https://linkedin.com/company/google",blog:"https://ai.google.dev/blog"},contactInfo:{support:"https://cloud.google.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"meta",name:"Meta",description:"Develops open-source Llama models, promoting accessible and efficient AI solutions for diverse applications.",website:"https://ai.meta.com",apiDocumentation:"https://ai.meta.com/llama/get-started",models:["llama-3.3-70b","llama3.1-8b","llama-4-maverick","llama-4-scout","llama-3.2-11b","llama-3.2-1b","llama-3.2-3b","llama-3.2-90b"],founded:"2004",headquarters:"Menlo Park, California, USA",ceo:"Mark Zuckerberg",employees:"86,482",funding:"Public Company",valuation:"$1.1T+",specialties:["Social Media","AI/ML","Virtual Reality","Open Source"],keyProducts:["Facebook","Instagram","WhatsApp","Llama","Oculus"],pricingModel:"open-source",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Hugging Face","PyTorch","ONNX"],useCases:["Research","Open Source Development","Social Media","VR/AR","Messaging"],certifications:["SOC 2","ISO 27001"],partnerships:["Microsoft","Amazon","Google"],socialMedia:{twitter:"https://twitter.com/MetaAI",linkedin:"https://linkedin.com/company/meta",blog:"https://ai.meta.com/blog"},contactInfo:{support:"https://developers.facebook.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"mistral",name:"Mistral AI",description:"Mistral AI is a French AI startup founded in 2023 by former researchers from Google DeepMind and Meta. Known for its open-source large language models, Mistral develops tools like Le Chat and La Plateforme, focusing on efficiency and accessibility. Recent projects include Mistral Small 3.1 and Codestral 22B. Stay updated with Mistral's latest news and innovations in the AI space.",website:"https://mistral.ai",apiDocumentation:"https://docs.mistral.ai",models:["mistral-8b","mistral-3b-latest","mistral-large","mistral-moderation-latest","mistral-saba-latest","mistral-small-latest","pixtral-large-latest","codestral","mistral-small-3.1-24b","ministral-8b"],founded:"2023",headquarters:"Paris, France",ceo:"Arthur Mensch",employees:"50+",funding:"$415M+",valuation:"$2B+",specialties:["Open Source AI","Large Language Models","Efficiency","Research"],keyProducts:["Mistral Large","Mistral Small","Le Chat","La Plateforme"],pricingModel:"hybrid",apiAccess:"public",supportedLanguages:["English","French","Multiple languages"],integrations:["Hugging Face","OpenAI Compatible","LangChain"],useCases:["Content Generation","Code Development","Research","Enterprise AI"],certifications:["GDPR Compliant"],partnerships:["Microsoft","AWS","Google Cloud"],socialMedia:{twitter:"https://twitter.com/MistralAI",linkedin:"https://linkedin.com/company/mistral-ai",github:"https://github.com/mistralai"},contactInfo:{support:"https://docs.mistral.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"deepseek",name:"DeepSeek",description:"DeepSeek, founded in 2023 in China, is making waves with its open-source AI models like DeepSeek-R1, known for strong coding and reasoning skills. Backed by High-Flyer Capital, it delivers powerful performance on a modest budget. With expanding projects in healthcare and natural language processing, DeepSeek continues to push innovation. Stay tuned for the latest DeepSeek news, updates, and breakthroughs.",website:"https://deepseek.ai",apiDocumentation:"https://deepseek.ai/docs",models:["deepseek-r1-llama-70b","deepseek-r1-qwen-32b","open-mistral-nemo","deepseek-r1","deepseek-v3-0324"],founded:"2023",headquarters:"Beijing, China",ceo:"Unknown",employees:"100+",funding:"$200M+",valuation:"$1B+",specialties:["Reasoning AI","Code Generation","Open Source","Research"],keyProducts:["DeepSeek R1","DeepSeek Coder","DeepSeek Chat"],pricingModel:"pay-per-use",apiAccess:"public",supp
1ortedLanguages:["English","Chinese","Multiple languages"],integrations:["Hugging Face","OpenAI Compatible"],useCases:["Code Development","Research","Reasoning","Content Generation"],certifications:["ISO 27001"],partnerships:["High-Flyer Capital"],socialMedia:{twitter:"https://twitter.com/deepseek_ai",linkedin:"https://linkedin.com/company/deepseek-ai",github:"https://github.com/deepseek-ai"},contactInfo:{support:"https://deepseek.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"perplexity",name:"Perplexity",description:"Perplexity AI, founded in 2022, is an AI-powered search engine offering conversational answers with real-time citations. It has apps, browser extensions, and plans for a new AI browser. With recent $500 million funding boosting its $14 billion valuation, Perplexity aims to reshape search. Stay updated on its innovations, partnerships, and legal challenges shaping the future of AI search technology.",website:"https://www.perplexity.ai",apiDocumentation:"https://docs.perplexity.ai",models:["perplexity-llama-3.1-sonar","perplexity-r1-1776","perplexity-sonar"],founded:"2022",headquarters:"San Francisco, California, USA",ceo:"Aravind Srinivas",employees:"100+",funding:"$500M+",valuation:"$14B+",specialties:["AI Search","Information Retrieval","Real-time Data","Conversational AI"],keyProducts:["Perplexity Search","Perplexity Pro","Perplexity API"],pricingModel:"hybrid",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Browser Extensions","Mobile Apps","API"],useCases:["Search","Re
1search","Information Retrieval","Q&A"],certifications:["SOC 2"],partnerships:["Anthropic","OpenAI"],socialMedia:{twitter:"https://twitter.com/perplexity_ai",linkedin:"https://linkedin.com/company/perplexity-ai",blog:"https://www.perplexity.ai/blog"},contactInfo:{support:"https://www.perplexity.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"qwen",name:"Qwen AI (Alibaba Cloud)",description:"Qwen AI by Alibaba Cloud is a powerful language model series launched in 2023, designed for diverse applications like smart assistants and business tools. With open-source models and strong industry adoption, Alibaba continues investing heavily in AI innovation. Stay updated on Qwen's latest advancements, collaborations, and breakthroughs shaping the future of AI technology worldwide.",website:"https://qwen.ai",apiDocumentation:"https://help.aliyun.com/document_detail/2400395.html",models:["qwen-2.5-32b","qwen-plus","qwen/qwen2.5-vl-32b-instruct:free"],founded:"1999 (Alibaba)",headquarters:"Hangzhou, China",ceo:"Daniel Zhang",employees:"254,941",funding:"Public Company",valuation:"$200B+",specialties:["E-commerce","Cloud Computing","AI/ML","Fintech"],keyProducts:["Qwen","Alibaba Cloud","Taobao","Tmall"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Chinese","Multiple languages"],integrations:["Alibaba Cloud","DingTalk","AliPay"],useCases:["E-commerce","Content Generation","Customer Service","Data Analysis"],certifications:["ISO 27001","SOC 2"],partnerships:["Microsoft","Intel","NVIDIA"],socialMedia:{twitter:"https://twitter.com/AlibabaCloud",linkedin:"https://linkedin.com/company/alibaba-group",blog:"https://www.alibabacloud.com/blog"},contactInfo:{support:"https://www.alibabacloud.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"flux",name:"Flux",description:"Flux is a future-focused technology company revolutionizing decentralized infrastructure with cutting-edge solutions. Known for projects like FluxOS and its integration with Kadena, the company empowers developers to build scalable, blockchain-powered applications. Over the years, Flux has evolved from a Web3 visionary to a trusted name in decentralized cloud services. Today, it continues to drive innovation through community-first tools and strategic partnerships. In recent news, Flux expanded its decentralized node network and collaborated with major DeFi platforms, reinforcing its commitment to building a more open, secure internet.",website:"https://flux.ai",apiDocumentation:"https://docs.flux.ai",models:["flux-vision-3.0","flux-text-2.5","flux-creative-1.0","flux-multimodal-pro"],founded:"2018",headquarters:"Amsterdam, Netherlands",ceo:"Daniel Keller",employees:"50+",funding:"$10M+",valuation:"$100M+",specialties:["Decentralized Infrastructure","Blockchain","AI/ML","Web3"],keyProducts:["FluxOS","Flux AI","Flux Cloud"],pricingModel:"subscription",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Kadena","DeFi Platforms","Blockchain Networks"],useCases:["Decentralized Computing","AI Development","Blockchain Applications","Web3"],certifications:["ISO 27001"],partnerships:["Kadena","Major DeFi Platforms"],socialMedia:{twitter:"https://twitter.com/Flux_AI",linkedin:"https://linkedin.com/company/flux-ai",github:"https://github.com/flux-ai"},contactInfo:{support:"https://flux.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"recraft",name:"Recraft",description:"Recraft is a next-generation AI design platform built to supercharge creativity. Launched to help creators craft stunning, scalable vector art and illustrations with ease, Recraft blends the power of artificial intelligence with intuitive design tools. In the past, the company has focused on empowering non-designers and professionals alike with smart features like style transfer, color harmonization, and real-time collaboration. Today, Recraft continues to evolveâoffering AI-driven design generation, custom branding assets, and seamless export options for everything from social media to web design.",website:"https://recraft.ai",apiDocumentation:"https://docs.recraft.ai",models:["recraft-designer-pro","recraft-illustrator","recraft-3d-gen","re
1craft-style-transfer"],founded:"2022",headquarters:"London, UK",ceo:"Unknown",employees:"50+",funding:"$20M+",valuation:"$100M+",specialties:["AI Design","Vector Graphics","Creative Tools","Branding"],keyProducts:["Recraft Designer","Recraft Illustrator","Recraft 3D"],pricingModel:"subscription",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Figma","Adobe","Canva","Social Media"],useCases:["Design","Branding","Marketing","Content Creation"],certifications:["ISO 27001"],partnerships:["Adobe","Figma"],socialMedia:{twitter:"https://twitter.com/recraft_ai",linkedin:"https://linkedin.com/company/recraft-ai",blog:"https://recraft.ai/blog"},contactInfo:{support:"https://recraft.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"ideogram",name:"Ideogram",description:"Ideogram is an innovative AI image generation company focused on turning text into visually stunning, coherent imagesâwith a special knack for rendering typography accurately. Founded by former Google Brain researchers, Ideogram combines deep learning expertise with an artistic edge to make creative expression more accessible and precise. In its early stages, Ideogram gained attention for solving a key challenge in AI image generation: producing legible, contextually relevant text within visuals.",website:"https://ideogram.ai",apiDocumentation:"https://docs.ideogram.ai",models:["ideogram-1.0","ideogram-pro","ideogram-typography","ideogram-photoreal"],founded:"2023",headquarters:"San Francisco, California, USA",ceo:"Unknown",employees:"20+",funding:"$20M+",valuation:"$100M+",specialties:["AI Image Generation","Typography","Creative AI","Visual Design"],keyProducts:["Ideogram Pro","Ideogram Typography","Ideogram Photoreal"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Design Tools","Social Media","Content Platforms"],useCases:["Image Generation","Typography","Marketing","Content Creation"],certifications:["ISO 27001"],partnerships:["Design Platforms"],socialMedia:{twitter:"https://twitter.com/ideogram_ai",linkedin:"https://linkedin.com/company/ideogram-ai",blog:"https://ideogram.ai/blog"},contactInfo:{support:"https://ideogram.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"luma",name:"Luma AI",description:"Luma AI is on a mission to make 3D accessible to everyone. Founded by a team of visionary engineers and creators, Luma uses cutting-edge neural rendering and AI technology to turn everyday photos and videos into lifelike 3D modelsâno special hardware or deep technical know-how required. Early on, Luma gained traction with its photorealistic 3D capture app, which empowered creators, developers, and filmmakers to digitize real-world objects and environments with incredible detail.",website:"https://lumalabs.ai",apiDocumentation:"https://docs.lumalabs.ai",models:["luma-ray2","luma-neural-3d","luma-photogrammetry","luma-avatar-gen"],founded:"2021",headquarters:"San Francisco, California, USA",ceo:"Unknown",employees:"50+",funding:"$50M+",valuation:"$200M+",specialties:["3D Generation","Neural Ren
1dering","Computer Vision","AR/VR"],keyProducts:["Luma Ray","Luma Neural 3D","Luma Photogrammetry"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Unity","Unreal Engine","Blender","3D Software"],useCases:["3D Modeling","AR/VR","Gaming","Film Production"],certifications:["ISO 27001"],partnerships:["Unity","Unreal Engine"],socialMedia:{twitter:"https://twitter.com/lumalabs",linkedin:"https://linkedin.com/company/luma-ai",blog:"https://lumalabs.ai/blog"},contactInfo:{support:"https://lumalabs.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"minmax",name:"MinMax",description:"MinMax is a forward-thinking AI company dedicated to optimizing decision-making through intelligent automation and data-driven insights. Founded by a team of machine learning experts and data scientists, MinMax started with a clear goal: help businesses make better choices faster. From early projects in predictive analytics and risk modeling, the company has grown into a trusted platform for real-time optimization in industries ranging from finance to logistics.",website:"https://minmax.ai",apiDocumentation:"https://docs.minmax.ai",models:["minmax-ultra","minmax-lite","minmax-multimodal","minmax-code"],founded:"2022",headquarters:"San Francisco, California, USA",ceo:"Unknown",employees:"30+",funding:"$15M+",valuation:"$50M+",specialties:["Decision Optimization","Predictive Analytics","Machine Learning","Business Intelligence"],keyProducts:["MinMax Ultra","MinMax Lite","MinMax Platform"],pricingModel:"enterprise",apiAccess:"enterprise-only",supportedLanguages:["English","Multiple languages"],integrations:["Business Intelligence Tools","ERP Systems","Analytics Platforms"],useCases:["Business Intelligence","Predictive Analytics","Risk Modeling","Optimization"],certifications:["ISO 27001","SOC 2"],partnerships:["Enterprise Software Companies"],socialMedia:{twitter:"https://twitter.com/minmax_ai",linkedin:"https://linkedin.com/company/minmax-ai",blog:"https://minmax.ai/blog"},contactInfo:{support:"https://minmax.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"hailuo",name:"Hailuo AI",description:"Hailuo AI is a rising force in the world of language and vision intelligence, focused on building multimodal AI that truly understands context, nuance, and meaning. Founded by a team of AI researchers and product innovators, Hailuo's mission is to create smarter, more intuitive systems that bridge the gap between human understanding and machine learning. The company first made waves with its work in contextual language modeling and image-text fusion, earning attention for its high-accuracy performance across real-world applications.",website:"https://hailuoai.com",apiDocumentation:"https://docs.hailuoai.com",models:["abab-6.5","hailuo-moe","hailuo-multimodal","hailuo-code"],founded:"2023",headquarters:"Beijing, China",ceo:"Unknown",employees:"50+",funding:"$30M+",valuation:"$100M+",specialties:["Multimodal AI","Language Models","Computer Vision","Context Understanding"],keyProducts:["Hailuo Multimodal","Hailuo Code","Hailuo Platform"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Chinese","Multiple languages"],integrations:["OpenAI Compatible","Hugging Face","LangChain"],useCases:["Content Generation","Image Understanding","Code Development","Research"],certifications:["ISO 27001"],partnerships:["Research Institutions","Tech Companies"],socialMedia:{twitter:"https://twitter.com/hailuo_ai",linkedin:"https://linkedin.com/company/hailuo-ai",github:"https://github.com/hailuo-ai"},contactInfo:{support:"https://hailuoai.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"alibaba",name:"Alibaba Cloud",description:"Alibaba Cloud is the cloud computing arm of Alibaba Group, providing a comprehensive suite of cloud services including AI and machine learning capabilities. With Qwen AI models and extensive cloud infrastructure, Alibaba Cloud serves millions of customers worldwide with enterprise-grade AI solutions.",website:"https://www.alibabacloud.com",apiDocumentation:"https://help.aliyun.com/document_detail/2400395.html",models:["qwen-2.5-32b","qwen-plus","qwen2.5-vl-32b-instruct"],founded:"2009",headquarters:"Hangzhou, China",ceo:"Daniel Zhang",employees:"254,941",funding:"Public Company",valuation:"$200B+",specialties:["Cloud Computing","AI/ML","E-commerce","Fintech"],keyProducts:["Alibaba Cloud","Qwen AI","DingTalk","AliPay"],pricingModel:"pay-per-use",apiAccess:"public",supp
1ortedLanguages:["English","Chinese","Multiple languages"],integrations:["Alibaba Cloud","DingTalk","AliPay"],useCases:["Cloud Computing","AI Development","E-commerce","Enterprise Solutions"],certifications:["ISO 27001","SOC 2"],partnerships:["Microsoft","Intel","NVIDIA"],socialMedia:{twitter:"https://twitter.com/AlibabaCloud",linkedin:"https://linkedin.com/company/alibaba-group",blog:"https://www.alibabacloud.com/blog"},contactInfo:{support:"https://www.alibabacloud.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"amazon-bedrock",name:"Amazon Bedrock",description:"Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies through a single API. It provides access to models from Anthropic, AI21, Cohere, Meta, and others, along with tools to build generative AI applications.",website:"https://aws.amazon.com/bedrock",apiDocumentation:"https://docs.aws.amazon.com/bedrock",models:["amazon-nova-pro","amazon-titan-premier","claude-3.5-sonnet","llama-3.3-70b"],founded:"2023",headquarters:"Seattle, Washington, USA",ceo:"Andy Jassy",employees:"1.5M+",funding:"Public Company",valuation:"$1.7T+",specialties:["Cloud Computing","AI/ML","Enterprise AI","Model Management"],keyProducts:["Amazon Bedrock","AWS","Amazon SageMaker"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["AWS Services","Lambda","S3","EC2"],useCases:["Enterprise AI","Model Management","AI Application Development","Cloud Computing"],certifications:["SOC 2","ISO 27001","FedRAMP","HIPAA"],partnerships:["Anthropic","Meta","AI21","Cohere"],socialMedia:{twitter:"https://twitter.com/awscloud",linkedin:"https://linkedin.com/company/amazon",blog:"https://aws.amazon.com/blogs/"},contactInfo:{support:"https://aws.amazon.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"azure",name:"Microsoft Azure",description:"Microsoft Azure is a comprehensive cloud computing platform that provides AI and machine learning services. With Azure OpenAI Service and Azure Cognitive Services, it offers enterprise-grade AI solutions with enterprise security and compliance features.",website:"https://azure.microsoft.com",apiDocumentation:"https://docs.microsoft.com/en-us/azure/",models:["gpt-4o","gpt-4o-mini","claude-3.5-sonnet","llama-3.3-70b"],founded:"2010",headquarters:"Redmond, Washington, USA",ceo:"Satya Nadella",employees:"221,000+",funding:"Public Company",valuation:"$2.8T+",specialties:["Cloud Computing","AI/ML","Enterprise Solutions","Security"],keyProducts:["Azure OpenAI Service","Azure Cognitive Services","Azure Machine Learning"],pricingModel:"pay-per-use",apiAccess:"enterprise",supportedLanguages:["English","Multiple languages"],integrations:["Microsoft 365","Power Platform","Dynamics 365"],useCases:["Enterprise AI","Cloud Computing","Business Applications","Security"],certifications:["SOC 2","ISO 27001","FedRAMP","HIPAA"],partnerships:["OpenAI","Meta","Anthropic"],socialMedia:{twitter:"https://twitter.com/Azure",linkedin:"https://linkedin.com/company/microsoft",blog:"https://azure.microsoft.com/en-us/blog/"},contactInfo:{support:"https://azure.microsoft.com/en-us/support/",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"cloudflare",name:"Cloudflare",description:"Cloudflare is a global cloud platform that provides AI and machine learning services through its Workers AI platform. It offers edge computing capabilities with AI models deployed globally for low-latency inference.",website:"https://www.cloudflare.com",apiDocumentation:"https://developers.cloudflare.com/workers-ai/",models:["llama-3.3-70b","mistral-large","gemini-2.0-flash"],founded:"2009",headquarters:"San Francisco, California, USA",ceo:"Matthew Prince",employees:"3,000+",funding:"Public Company",valuation:"$30B+",specialties:["Edge Computing","AI/ML","Security","CDN"],keyProducts:["Workers AI","Cloudflare Workers","Cloudflare CDN"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Cloudflare Workers","Cloudflare Pages","Cloudflare R2"],useCases:["Edge AI","
1Low-latency Inference","Global AI Deployment","Web Security"],certifications:["SOC 2","ISO 27001","GDPR Compliant"],partnerships:["Meta","Mistral","Google"],socialMedia:{twitter:"https://twitter.com/cloudflare",linkedin:"https://linkedin.com/company/cloudflare",blog:"https://blog.cloudflare.com/"},contactInfo:{support:"https://support.cloudflare.com/",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"cohere",name:"Cohere",description:"Cohere is an AI company that provides enterprise-grade language models and NLP tools. Founded by former Google researchers, Cohere focuses on making AI accessible to businesses through simple APIs and powerful language understanding capabilities.",website:"https://cohere.ai",apiDocumentation:"https://docs.cohere.com",models:["cohere-command","cohere-command-light","cohere-embed"],founded:"2019",headquarters:"Toronto, Canada",ceo:"Aidan Gomez",employees:"200+",funding:"$435M+",valuation:"$2.2B+",specialties:["Language Models","NLP","Enterprise AI","Text Generation"],keyProducts:["Cohere Command","Cohere Embed","Cohere Classify"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["LangChain","Hugging Face","OpenAI Compatible"],useCases:["Text Generation","Semantic Search","Content Classification","Customer Support"],certifications:["SOC 2","GDPR Compliant"],partnerships:["Anthropic","AWS","Google Cloud"],socialMedia:{twitter:"https://twitter.com/cohere_ai",linkedin:"https://linkedin.com/company/cohere-ai",blog:"https://txt.cohere.com/"},contactInfo:{support:"https://cohere.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"google-ai-studio",name:"Google AI Studio",description:"Google AI Studio is a platform for building and deploying AI applications using Google's latest models. It provides tools for prompt engineering, model fine-tuning, and application development with access to models like Gemini and Gemma.",website:"https://aistudio.google.com",apiDocumentation:"https://aistudio.google.com/docs",models:["gemini-2.0-flash","gemini-2.0-pro","gemma-3-4b","gemma-3-12b"],founded:"2023",headquarters:"Mountain Vie
1w, California, USA",ceo:"Sundar Pichai",employees:"156,500+",funding:"Public Company",valuation:"$1.8T+",specialties:["AI Development","Model Deployment","Prompt Engineering","Fine-tuning"],keyProducts:["Google AI Studio","Gemini Models","Gemma Models"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Google Cloud","Firebase","Vertex AI"],useCases:["AI Application Development","Model Fine-tuning","Prompt Engineering","Prototyping"],certifications:["SOC 2","ISO 27001"],partnerships:["OpenAI","Anthropic","Meta"],socialMedia:{twitter:"https://twitter.com/GoogleAI",linkedin:"https://linkedin.com/company/google",blog:"https://ai.google.dev/blog"},contactInfo:{support:"https://aistudio.google.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"google-vertex",name:"Google Vertex AI",description:"Google Vertex AI is a managed machine learning platform that provides tools for building, deploying, and managing ML models at scale. It offers pre-trained models, custom model training, and MLOps capabilities for enterprise AI development.",website:"https://cloud.google.com/vertex-ai",apiDocumentation:"https://cloud.google.com/vertex-ai/docs",models:["gemini-2.0-flash","gemini-2.0-pro","gemini-2.5-pro","gemma-3-4b"],founded:"2021",headquarters:"Mountain Vie
1w, California, USA",ceo:"Sundar Pichai",employees:"156,500+",funding:"Public Company",valuation:"$1.8T+",specialties:["Machine Learning","MLOps","Model Training","Enterprise AI"],keyProducts:["Vertex AI","Vertex AI Studio","Vertex AI Pipelines"],pricingModel:"pay-per-use",apiAccess:"enterprise",supportedLanguages:["English","Multiple languages"],integrations:["Google Cloud","BigQuery","Cloud Storage"],useCases:["ML Model Development","Model Training","MLOps","Enterprise AI"],certifications:["SOC 2","ISO 27001","FedRAMP"],partnerships:["OpenAI","Anthropic","Meta"],socialMedia:{twitter:"https://twitter.com/GoogleCloud",linkedin:"https://linkedin.com/company/google",blog:"https://cloud.google.com/blog/"},contactInfo:{support:"https://cloud.google.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"groq",name:"Groq",description:"Groq is a technology company that provides ultra-fast AI inference through its custom hardware and software stack. Known for its LPU (Language Processing Unit) technology, Groq delivers sub-millisecond latency for large language models, making real-time AI applications possible.",website:"https://groq.com",apiDocumentation:"https://console.groq.com/docs",models:["llama-3.3-70b","gemini-2.0-flash","mistral-large","mixtral-8x7b"],founded:"2016",headquarters:"Mountain Vie
1w, California, USA",ceo:"Jonathan Ross",employees:"100+",funding:"$367M+",valuation:"$1B+",specialties:["Ultra-fast Inference","Custom Hardware","Low Latency","Real-time AI"],keyProducts:["Groq LPU","Groq API","Groq Cloud"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["OpenAI Compatible","LangChain","Hugging Face"],useCases:["Real-time AI","Low-latency Applications","Interactive AI","Edge Computing"],certifications:["SOC 2","ISO 27001"],partnerships:["Meta","Google","Mistral"],socialMedia:{twitter:"https://twitter.com/groq_inc",linkedin:"https://linkedin.com/company/groq-inc",blog:"https://groq.com/blog"},contactInfo:{support:"https://groq.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"kluster-ai",name:"Kluster.ai",description:"Kluster.ai is an AI company focused on providing enterprise-grade AI solutions for business intelligence and analytics. It offers tools for data analysis, predictive modeling, and automated insights generation using advanced machine learning techniques.",website:"https://kluster.ai",apiDocumentation:"https://docs.kluster.ai",models:["kluster-analytics","kluster-predict","kluster-insights"],founded:"2022",headquarters:"San Francisco, California, USA",ceo:"Unknown",employees:"50+",funding:"$20M+",valuation:"$100M+",specialties:["Business Intelligence","Predictive Analytics","Data Analysis","Machine Learning"],keyProducts:["Kluster Analytics","Kluster Predict","Kluster Insights"],pricingModel:"enterprise",apiAccess:"enterprise-only",supportedLanguages:["English","Multiple languages"],integrations:["Business Intelligence Tools","Data Warehouses","CRM Systems"],useCases:["Business Intelligence","Predictive Analytics","Data Analysis","Automated Insights"],certifications:["ISO 27001","SOC 2"],partnerships:["Enterprise Software Companies"],socialMedia:{twitter:"https://twitter.com/kluster_ai",linkedin:"https://linkedin.com/company/kluster-ai",blog:"https://kluster.ai/blog"},contactInfo:{support:"https://kluster.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"lambda",name:"Lambda",description:"Lambda is a cloud computing company that provides GPU-powered cloud infrastructure for AI and machine learning workloads. It offers cost-effective GPU instances and specialized hardware for training and inference of large language models.",website:"https://lambdalabs.com",apiDocumentation:"https://docs.lambdalabs.com",models:["custom-deployment","gpu-instances","specialized-hardware"],founded:"2012",headquarters:"San Francisco, California, USA",ceo:"Stephen Balaban",employees:"100+",funding:"$50M+",valuation:"$200M+",specialties:["GPU Computing","Cloud Infrastructure","AI Training","Cost Optimization"],keyProducts:["Lambda Cloud","Lambda GPU Instances","Lambda Workstation"],pricingModel:"pay-per-use",apiAccess:"public",supportedLanguages:["English","Multiple languages"],integrations:["Docker","Kubernetes","ML Frameworks"],useCases:["AI Model Training","GPU Computing","Machine Learning","Data Science"],certifications:["SOC 2","ISO 27001"],partnerships:["NVIDIA","AMD","Intel"],socialMedia:{twitter:"https://twitter.com/lambdalabs",linkedin:"https://linkedin.com/company/lambda-labs",blog:"https://lambdalabs.com/blog"},contactInfo:{support:"https://lambdalabs.com/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"openinference",name:"OpenInference",description:"OpenInference is an open-source project focused on standardizing AI model inference and observability. It provides tools for monitoring, tracing, and debugging AI applications, making it easier to deploy and manage AI models in production environments.",website:"https://openinference.io",apiDocumentation:"https://docs.openinference.io",models:["monitoring-tools","tracing-framework","debugging-tools"],founded:"2023",headquarters:"Open Source",ceo:"Open Source",employees:"Community",funding:"Open Source",valuation:"Open Source",specialties:["AI Observability","Model Monitoring","Open Source","Production AI"],keyProducts:["OpenInference Monitoring","OpenInference Tracing","OpenInference Debugging"],pricingModel:"open-source",apiAccess:"public",supp
1ortedLanguages:["English","Multiple languages"],integrations:["OpenAI","Anthropic","LangChain","MLflow"],useCases:["AI Model Monitoring","Production Debugging","Performance Optimization","Observability"],certifications:["Open Source"],partnerships:["Open Source Community"],socialMedia:{github:"https://github.com/openinference",blog:"https://openinference.io/blog"},contactInfo:{support:"https://github.com/openinference",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"},{id:"xai",name:"xAI",description:"xAI is an artificial intelligence company founded by Elon Musk, focused on developing AI systems that are truthful and beneficial to humanity. The company aims to understand the true nature of the universe through AI research and development.",website:"https://x.ai",apiDocumentation:"https://docs.x.ai",models:["grok-beta","grok-2","grok-ultra"],founded:"2023",headquarters:"Austin, Texas, USA",ceo:"Elon Musk",employees:"100+",funding:"$6B+",valuation:"$18B+",specialties:["AI Research","Truthful AI","Large Language Models","AI Safety"],keyProducts:["Grok","Grok Beta","Grok Ultra"],pricingModel:"subscription",apiAccess:"waitlist",supportedLanguages:["English","Multiple languages"],integrations:["X Platform","Tesla","SpaceX"],useCases:["AI Research","Truthful Information","AI Safety","Research Applications"],certifications:["In Development"],partnerships:["X Platform","Tesla"],socialMedia:{twitter:"https://twitter.com/xai",linkedin:"https://linkedin.com/company/xai-ai",blog:"https://x.ai/blog"},contactInfo:{support:"https://x.ai/support",email:"[email protected]"},status:"beta",lastUpdated:"2024-12-01"},{id:"zai",name:"Z.AI",description:"Z.AI is an AI company focused on developing advanced language models and AI solutions for enterprise applications. It provides tools for natural language processing, content generation, and AI-powered business automation.",website:"https://z.ai",apiDocumentation:"https://docs.z.ai",models:["zai-language","zai-content","zai-automation"],founded:"2022",headquarters:"San Francisco, California, USA",ceo:"Unknown",employees:"50+",funding:"$30M+",valuation:"$150M+",specialties:["Language Models","Content Generation","Business Automation","NLP"],keyProducts:["Z.AI Language","Z.AI Content","Z.AI Automation"],pricingModel:"enterprise",apiAccess:"enterprise-only",supportedLanguages:["English","Multiple languages"],integrations:["Business Platforms","CRM Systems","Content Management"],useCases:["Content Generation","Business Automation","Customer Support","Data Analysis"],certifications:["ISO 27001","SOC 2"],partnerships:["Enterprise Software Companies"],socialMedia:{twitter:"https://twitter.com/zai_ai",linkedin:"https://linkedin.com/company/zai-ai",blog:"https://z.ai/blog"},contactInfo:{support:"https://z.ai/support",email:"[email protected]"},status:"active",lastUpdated:"2024-12-01"}],a=[{id:"gpt-4o",name:"GPT-4o",provider:"OpenAI",description:"OpenAI's most advanced multimodal model, capable of processing and generating text, images, and potentially other data types in real-time. It features a 128,000-token context window, delivering improved reasoning, reduced latency, and enhanced instruction-following compared to previous models. GPT-4o achieves state-of-the-art performance across benchmarks like MMLU and excels in applications requiring real-time interaction, such as conversational agents, creative writing, and multimodal analysis.",category:["General Purpose","Multimodal"],tags:["new","featured","high_context"],strengths:["Advanced reasoning","Real-time multimodal processing","Long context handling","Code generation","Instruction following"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:5,output:15},documentation:"https://platform.openai.com/docs/models/gpt-4o"},{id:"gpt-4o-mini",name:"GPT-4o Mini",provider:"OpenAI",description:"A compact, cost-efficient variant of GPT-4o, retaining 70% of its multimodal performance with a 128,000-token context window. It supports text generation, image understanding, and code generation at a fraction of the cost, making it ideal for budget-conscious applications like lightweight chatbots, content generation, and educational tools. GPT-4o Mini balances performance and affordability while maintaining strong reasoning capabilities.",category:["General Purpose","Multimodal"],tags:["new","cost_effective"],strengths:["Cost effectiveness","Balanced multimodal capabilities","Image understanding","Code generation"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.15,output:.6},documentation:"https://platform.openai.com/docs/models"},{id:"o3-mini",name:"O3 Mini",provider:"OpenAI",description:"A highly efficie
1nt, affordable model designed for everyday tasks, featuring a 32,000-token context window. O3 Mini excels in rapid text and code generation with basic reasoning capabilities, making it perfect for high-volume applications such as customer support chatbots, automated responses, and simple scripting tasks. Its low cost and fast processing speed ensure scalability for routine operations.",category:["General Purpose"],tags:["new","cost_effective"],strengths:["Speed and efficiency","Cost effectiveness","Good reasoning"],contextSize:"32,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.1,output:.4},documentation:"https://platform.openai.com/docs/models"},{id:"o1",name:"O1",provider:"OpenAI",description:"OpenAI's powerful reasoning-focused model with exceptional understanding of complex tasks and nuanced instructions. With a massive context window of 1,000,000 tokens, it offers unprecedented depth in analysis and generation capabilities. O1 excels at multi-step reasoning, complex problem-solving, and handling extended conversations with retention of subtle details.",category:["General Purpose"],tags:["new","featured","high_context"],strengths:["Exceptional reasoning","Ultra-long context handling","Complex instruction following","Memory retention","Advanced problem-solving"],contextSize:"1,000,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:15,output:75},documentation:"https://platform.openai.com/docs/models"},{id:"gpt-4.5-preview",name:"GPT-4.5 Preview",provider:"OpenAI",description:"A preview release of OpenAI's next-generation model, offering enhanced reasoning, instruction following, and knowledge compared to GPT-4o. With a 128,000-token context window, it brings improved consistency in outputs and better handling of complex, multi-step tasks. This model represents an interim advancement toward future capabilities while maintaining API compatibility with existing applications.",category:["General Purpose","Multimodal"],tags:["new","preview","high_context"],strengths:["Enhanced reasoning","Improved factual accuracy","Better instruction following","Complex task handling"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:10,output:30},documentation:"https://platform.openai.com/docs/models"},{id:"quasar-alpha",name:"Quasar Alpha",provider:"OpenAI",description:"A powerful, experimental long-context foundation model with a massive 1,000,000 token context window. Quasar Alpha excels at processing and reasoning over extensive documents, code repositories, and multi-part instructions, making it ideal for research, complex analysis, and tasks requiring integration of information across vast amounts of content.",category:["General Purpose"],tags:["new","experimental","ultra_high_context"],strengths:["Massive context length","Comprehensive document analysis","Extended reasoning chains","Source integration"],contextSize:"1,000,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:10,output:30},documentation:"https://platform.openai.com/docs/models"},{id:"text-embedding-3-small",name:"Text Embedding 3 Small",provider:"OpenAI",description:"A cost-effective embedding model designed for efficient text representation and semantic search applications. It converts text into numerical vectors that capture semantic meaning, enabling similarity comparisons, clustering, and classification. This compact model balances performance and efficiency for production-level semantic search, recommendation systems, and content organization.",category:["Embedding"],tags:["cost_effective","production_ready"],strengths:["Semantic search optimization","Efficient document retrieval","Text similarity calculations","Content clustering"],contextSize:"8,191 tokens",capabilities:{textGeneration:!1,imageUnderstanding:!1,codeGeneration:!1,functionCalling:!1,reasoning:!1,webSearch:!1},pricing:{input:.02,output:0},documentation:"https://platform.openai.com/docs/guides/embeddings"},{id:"claude-3.7-sonnet",name:"Claude 3.7 Sonnet",provider:"Anthropic",description:"Anthropic's flagship model introducing 'visible thinking,' which displays its reasoning process in real-time for enhanced transparency. With a 200,000-token context window, it offers top-tier reasoning, coding, and multimodal capabilities (text and images). Claude 3.7 Sonnet excels in complex tasks like softw
1are development, data analysis, and problem-solving, with low hallucination rates and robust safety features, making it a trusted choice for critical applications.",category:["General Purpose","Multimodal"],strengths:["Advanced reasoning","Visible thinking transparency","Superior code generation","Image understanding","Low hallucination rate"],contextSize:"200,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:5,output:20},documentation:"https://www.anthropic.com/claude/sonnet"},{id:"claude-3.5-sonnet",name:"Claude 3.5 Sonnet",provider:"Anthropic",description:"A highly capable Anthropic model with a 200,000-token context window, offering exceptional reasoning, coding, and multimodal (text and image) performance. It includes advanced safety guardrails and improved multilingual support, making it suitable for secure, complex tasks like legal analysis, technical writing, and visual data interpretation. Claude 3.5 Sonnet is known for its low hallucination rate and precise outputs.",category:["General Purpose","Multimodal"],strengths:["Strong reasoning","Low hallucination rate","Image understanding","Code generation","Long context handling"],contextSize:"200,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:3,output:15},documentation:"https://docs.anthropic.com/claude/docs/models-overview"},{id:"claude-3.5-haiku-new",name:"Claude 3.5 Haiku New",provider:"Anthropic",description:"An upgraded version of Claude 3.5 Haiku with a 200,000-token context window, featuring improved reasoning, coding, and visual understanding. It retains the original's speed and cost-efficiency while enhancing performance on complex prompts, making it suitable for advanced real-time applications like technical support, code review, and detailed image-based tasks.",category:["General Purpose","Multimodal"],strengths:["Speed and efficiency","Cost effectiveness","Image understanding","Enhanced reasoning"],contextSize:"200,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.25,output:1.25},documentation:"https://docs.anthropic.com/claude/docs/models-overview"},{id:"claude-3.5-haiku",name:"Claude 3.5 Haiku",provider:"Anthropic",description:"A balanced model in Anthropic's Claude 3.5 family, blending performance and efficiency with a 48,000-token context window. It delivers strong reasoning, factual accuracy, and balanced abilities across tasks like content generation, summarization, and basic coding. Claude 3.5 Haiku offers enhanced performance over previous generations while maintaining cost-effectiveness, making it suitable for personal productivity and everyday business applications.",category:["General Purpose","Multimodal"],strengths:["Cost effectiveness","Fast response time","Quality reasoning","Balanced capabilities"],contextSize:"48,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.25,output:1.25},documentation:"https://www.anthropic.com/claude/haiku"},{id:"claude-3.5-sonnet-v2.0",name:"Claude 3.5 Sonnet v2.0",provider:"Anthropic",description:"An updated version of Anthropic's Claude 3.5 Sonnet model with enhanced reasoning capabilities and reduced hallucinations. It maintains the 200,000-token context window while providing improved performance on complex tasks, better instruction following, and more consistent outputs. This version offers refined capabilities for enterprise applications, professional content creation, and advanced reasoning tasks.",category:["General Purpose","Multimodal"],tags:["new","updated"],strengths:["Enhanced reasoning","Reduced hallucinations","Improved consistency","Better instruction following"],contextSize:"200,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:3,output:15},documentation:"https://www.anthropic.com/claude/sonnet"},{id:"amazon-nova-pro",name:"Amazon Nova Pro",provider:"Amazon",de
1scription:"A premium multimodal model from Amazon's Nova family, featuring a 300,000-token context window and top-tier accuracy, speed, and cost-efficiency. It excels in processing text, images, and videos with advanced reasoning, making it ideal for agentic workflows, enterprise analytics, and complex multimodal tasks like video summarization and document processing.",category:["General Purpose","Multimodal"],strengths:["Instruction following","Image and video understanding","Long context handling","Cost effectiveness"],contextSize:"300,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.06,output:.24},documentation:"https://aws.amazon.com/bedrock/nova/"},{id:"amazon-titan-premier",name:"Amazon Titan Premier",provider:"Amazon",description:"A high-performance model from Amazon's Titan family with a 128,000-token context window, designed for enterprise applications. It offers complex reasoning, enhanced guardrails, and customization options, excelling in retrieval-augmented generation (RAG) and agent-based workflows in secure environments like financial analysis and compliance monitoring.",category:["General Purpose"],strengths:["Advanced reasoning","Enterprise applications","Long context handling","Cost effectiveness"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.08,output:.32},documentation:"https://aws.amazon.com/bedrock/titan/"},{id:"nova-lite",name:"Nova Lite",provider:"Amazon",description:"A cost-effective multimodal model from Amazon's Nova family with a 128,000-token context window, optimized for high-throughput tasks. It supports text, image, and video processing, making it suitable for applications like customer interactions, document analysis, and lightweight visual content generation, all at a competitive price point.",category:["General Purpose","Multimodal"],strengths:["Cost effectiveness","Speed and efficiency","Basic image understanding"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.06,output:.24},documentation:"https://aws.amazon.com/bedrock/nova/"},{id:"nova-micro",name:"Nova Micro",provider:"Amazon",description:"An ultra-efficient text-only model from Amazon's Nova family with a 128,000-token context window, designed for low-latency, high-throughput text processing. It's ideal for simple tasks like chatbots, text summarization, and automated responses in cost-sensitive scenarios, offering minimal overhead and maximum scalability.",category:["General Purpose"],strengths:["Speed and efficiency","Cost effectiveness","High throughput"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.04,output:.14},documentation:"https://aws.amazon.com/bedrock/nova/"},{id:"titan-express",name:"Titan Express",provider:"Amazon",description:"A fast, economical text model from Amazon's Titan family with an 8,000-token context window, tailored for high-volume text processing. It provides reliable performance for enterprise use cases like conversational chat, text generation, and basic automation, balancing speed and cost-efficiency effectively.",category:["General Purpose"],strengths:["Speed and efficiency","Cost effectiveness","Enterprise applications"],contextSize:"8,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.03,output:.12},documentation:"https://aws.amazon.com/bedrock/titan/"},{id:"titan-lite",name:"Titan Lite",provider:"Amazon",description:"An ultra-lightweight text model from Amazon's Titan family with a 4,000-token context window, offering basic text processing at the lowest cost. It's optimized for simple, high-volume applications like short
1-form content generation and lightweight chatbots, prioritizing affordability and efficiency.",category:["General Purpose"],strengths:["Cost effectiveness","Speed and efficiency","Basic reasoning"],contextSize:"4,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!1,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.02,output:.08},documentation:"https://aws.amazon.com/bedrock/titan/"},{id:"gemini-2.0-flash",name:"Gemini 2.0 Flash",provider:"Google",description:"A fast, efficient multimodal model from Google's Gemini 2.0 family with a 128,000-token context window, supporting text, image, and basic video understanding. It delivers strong performance for everyday tasks like content creation, image analysis, and quick coding, offering a cost-effective solution with excellent speed and scalability.",category:["General Purpose","Multimodal"],strengths:["Cost effectiveness","Speed and efficiency","Balanced multimodal capabilities"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.35,output:1.05},documentation:"https://ai.google.dev/models/gemini"},{id:"gemini-2.0-pro",name:"Gemini 2.0 Pro",provider:"Google",description:"Google's flagship model in the Gemini 2.0 family, combining strong reasoning, multimodal understanding, and extensive knowledge with a 128,000-token context window. It excels in complex tasks demanding sophisticated reasoning, such as in-depth analysis, nuanced content creation, and advanced coding projects. Gemini 2.0 Pro offers balanced capabilities across text, code, and image understanding, making it well-suited for professional applications and development workflows.",category:["General Purpose","Multimodal"],strengths:["Sophisticated reasoning","Balanced multimodal abilities","Strong coding capabilities","Nuanced content generation"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:3.5,output:10.5},documentation:"https://ai.google.dev/models/gemini"},{id:"gemini-2.5-pro",name:"Gemini 2.5 Pro",provider:"Google",description:"Google's advanced next-generation multimodal model with an exceptional 1,000,000 token context window, capable of handling massive inputs including entire books, legal files, or multimedia content. It offers improved reasoning, better instruction following, and enhanced capabilities across text, image, audio and video processing. The model excels at complex problem-solving, extensive document analysis, and creative content generation with remarkable consistency and factual accuracy.",category:["General Purpose","Multimodal"],tags:["new","featured","ultra_high_context"],strengths:["Massive context window","Enhanced reasoning","Multimodal understanding","Complex document analysis","Superior instruction following"],contextSize:"1,000,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:7,output:21},documentation:"https://ai.google.dev/models/gemini"},{id:"gemini-2.0-flash-exp-image-generation",name:"Gemini 2.0 Flash Image Generation",provider:"Google",description:"An experimental Gemini model specialized in text-to-image generation capabilities with a 32,000-token context window. It converts detailed text prompts into high-quality, creative images with strong understanding of styles, concepts, and composition. This model bridges text understanding and visual creation, making it ideal for creative professionals, marketing content generation, and visual prototyping.",category:["Multimodal","Image Generation"],tags:["experimental","new"],strengths:["Text-to-image generation","Style understanding","Visual creativity","Compositional awareness"],contextSize:"32,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!1,functionCalling:!1,reasoning:!0,webSearch:!1},pricing:{input:.35,output:1.05},documentation:"https://ai.google.dev/models/gemini"},{id:"gemma-3-4b",name:"Gemma 3 4B",provider:"Google",description:"A compact multimodal model from Google's Gemma 3 family with a 128,000-token context window, capable of processing both text and images. It provides efficie
1nt performance for everyday tasks with minimal computational requirements, making it ideal for lightweight applications, personal projects, and educational tools where deployment efficiency is prioritized over maximum capability.",category:["General Purpose","Multimodal"],tags:["efficient","multimodal","open_weights"],strengths:["Deployment efficiency","Basic multimodal capabilities","Long context handling","Balanced performance"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!1,reasoning:!0,webSearch:!1},pricing:{input:.1,output:.3},documentation:"https://ai.google.dev/gemma"},{id:"gemma-3-12b",name:"Gemma 3 12B",provider:"Google",description:"A mid-sized multimodal model in Google's Gemma 3 family with a 128,000-token context window, offering an excellent balance of performance and efficiency. It provides strong reasoning and multimodal capabilities for a wide range of applications, from content creation and analysis to development and research projects, with reasonable computational requirements.",category:["General Purpose","Multimodal"],tags:["balanced","multimodal","open_weights"],strengths:["Balanced performance","Strong reasoning","Multimodal processing","Development versatility"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.3,output:.9},documentation:"https://ai.google.dev/gemma"},{id:"gemma-3-27b",name:"Gemma 3 27B",provider:"Google",description:"The largest model in Google's Gemma 3 family with a 128,000-token context window, offering advanced multimodal capabilities for processing text and images. It delivers sophisticated reasoning, nuanced content generation, and robust code understanding, making it ideal for professional applications, research, and complex tasks requiring depth of analysis and substantial computational resources.",category:["General Purpose","Multimodal"],tags:["advanced","multimodal","open_weights"],strengths:["Advanced reasoning","Sophisticated multimodal processing","Superior code generation","Complex task handling"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.5,output:1.5},documentation:"https://ai.google.dev/gemma"},{id:"llama-3.3-70b",name:"Llama 3.3 70B",provider:"Meta",description:"The flagship model in Meta's Llama 3.3 family with a 128,000-token context window, designed for enterprise and research applications. It delivers state-of-the-art performance across reasoning, coding, and language understanding, with enhanced multilingual support and robust safety guardrails. Llama 3.3 70B excels in complex tasks like detailed content creation, technical problem-solving, and advanced applications requiring sophisticated reasoning.",category:["General Purpose"],strengths:["Superior reasoning","Advanced coding","Multilingual support","Context understanding","Instruction following"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:1.5,output:6},documentation:"https://llama.meta.com/docs/"},{id:"llama3.1-8b",name:"Llama 3.1 8B",provider:"Meta",description:"An efficient open-weight model from Meta's Llama 3.1 family with an 8,000-token context window, optimized for accessibility and local deployment. It provides strong performance with improved multilingual support and instruction following, ideal for cost-effective solutions like lightweight chatbots, educational tools, and on-device AI applications.",category:["General Purpose"],strengths:["Open weights","Efficiency","Local deployment","Basic reasoning"],contextSize:"8,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.1,output:.3},documentation:"https://ai.meta.com/llama/get-started"},{id:"llama-4-maverick",name:"Llama 4 Maverick",provider:"Meta",description:"A sophisticated multimodal mixture-of-experts model from Meta with a 10,000,000-token context window, offering unprecedented document processing capabilities. It excels in multimodal understanding, processing text and images with exceptional reasoning and knowledge. As Meta's most advanced model, it delivers superior performance for enterprise applications, research, and complex analytical tasks.",category:["General Purpose","Multimodal"],tags:["new","featured","ultra_high_context","moe"],strengths:["Massive context window","Superior multimodal capabilities","Expert-level reasoning","Advanced code generation"],contextSize:"10,000,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:5,output:15},documentation:"https://llama.com/docs/model-cards-and-prompt-formats/llama4_omni/"},{id:"llama-4-scout",name:"Llama 4 Scout",provider:"Meta",description:"A balanced multimodal mixture-of-experts model from Meta with a 10,000,000-token context window, offering comprehensive document processing capabilities. It provides strong multimodal understanding of text and images with 17 billion active parameters across 16 expert modules. This model delivers excellent performance for general applications requiring robust reasoning and image analysis.",category:["General Purpose","Multimodal"],tags:["new","ultra_high_context","moe"],strengths:["Massive context window","Strong multimodal capabilities","Balanced performance","Efficient processing"],contextSize:"10,000,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!0,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:2,output:6},documentation:"https://llama.com/docs/model-cards-and-prompt-formats/llama4_omni/"},{id:"llama-3.2-11b",name:"Llama 3.2 11B",provider:"Meta",description:"A mid-sized model from Meta's Llama 3.2 family with a 128,000-token context window, offering improved reasoning and instruction following. It provides strong performance across general tasks with efficie
1nt resource utilization, making it suitable for applications requiring a balance of capability and deployment efficiency.",category:["General Purpose"],strengths:["Balanced performance","Efficient resource usage","Strong reasoning","Long context handling"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.3,output:.9},documentation:"https://ai.meta.com/llama/"},{id:"llama-3.2-1b",name:"Llama 3.2 1B",provider:"Meta",description:"A highly compact model from Meta's Llama 3.2 family with a 32,000-token context window, designed for resource-constrained environments. It offers surprisingly strong performance for its size, making it ideal for edge devices, on-device applications, and scenarios requiring minimal computational resources.",category:["General Purpose"],tags:["efficient","compact"],strengths:["Extreme efficiency","Edge deployment","Low resource requirements","Fast inference"],contextSize:"32,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!1,reasoning:!0,webSearch:!1},pricing:{input:.05,output:.15},documentation:"https://ai.meta.com/llama/"},{id:"llama-3.2-3b",name:"Llama 3.2 3B",provider:"Meta",description:"A lightweight model from Meta's Llama 3.2 family with a 64,000-token context window, offering impressive capabilities for its compact size. It balances efficiency and performance for applications requiring local deployment or constrained resources while maintaining reasonable context handling and reasoning abilities.",category:["General Purpose"],tags:["efficient","compact"],strengths:["Deployment efficiency","Good context handling","Basic reasoning","Fast response time"],contextSize:"64,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.1,output:.3},documentation:"https://ai.meta.com/llama/"},{id:"llama-3.2-90b",name:"Llama 3.2 90B",provider:"Meta",description:"The largest model in Meta's Llama 3.2 family with a 128,000-token context window, offering exceptional reasoning, instruction following, and knowledge encoding. It delivers state-of-the-art performance for complex tasks requiring sophisticated analysis, detailed content generation, and technical problem-solving, making it suitable for research and enterprise applications.",category:["General Purpose"],tags:["advanced","high_performance"],strengths:["Superior reasoning","Advanced knowledge encoding","Technical expertise","Complex task handling"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:2,output:8},documentation:"https://ai.meta.com/llama/"},{id:"mistral-large",name:"Mistral Large",provider:"Mistral",description:"Mistral AI's flagship model with a 32,000-token context window, delivering exceptional performance across reasoning, coding, and knowledge-intensive tasks. It achieves top-tier scores on the MMLU benchmark (81.2%) and excels in complex reasoning, detailed content creation, and technical problem-solving, making it ideal for advanced applications in research, enterprise, and professional content generation.",category:["General Purpose"],strengths:["Advanced reasoning","Complex problem-solving","Superior code generation","Knowledge breadth"],contextSize:"32,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:8,output:24},documentation:"https://docs.mistral.ai"},{id:"mistral-small-3.1-24b",name:"Mistral Small 3.1 24B",provider:"Mistral",description:"A mid-sized model from Mistral AI's 3.1 series with a 32,000-token context window, offering strong performance with improved reasoning and instruction following. It provides an excellent balance between capability and cost, making it suitable for a wide range of production applications including content generation, customer support, and technical assistance.",category:["General Purpose"],tags:["new","balanced"],strengths:["Cost-effective performance","Balanced capabilities","Strong instruction following","Quality reasoning"],contextSize:"32,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:2,output:6},documentation:"https://docs.mistral.ai"},{id:"ministral-8b",name:"Ministral 8B",provider:"Mistral",description:"A compact model from Mistral AI with an 8,000-token context window, designed for efficiency and accessibility. It provides solid performance for everyday tasks with minimal computational requirements, making it ideal for lightweight applications, personal tools, and scenarios requiring balanced performance and resource efficiency.",category:["General Purpose"],tags:["efficie
1nt","compact"],strengths:["Deployment efficiency","Speed","Basic reasoning","Cost effectiveness"],contextSize:"8,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.15,output:.45},documentation:"https://docs.mistral.ai"},{id:"deepseek-r1-llama-70b",name:"DeepSeek R1 Llama 70B",provider:"DeepSeek",description:"A large reasoning-focused model with a 128,000-token context window, built on the Llama architecture. It specializes in logical analysis, problem-solving, and handling complex multi-step reasoning chains, particularly for technical and analytical tasks. DeepSeek R1 Llama 70B excels in applications requiring depth of analysis, such as research assistance, technical Q&A, and complex data interpretation.",category:["Reasoning","General Purpose"],strengths:["Advanced reasoning","Step-by-step problem-solving","Technical analysis","Complex task handling"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:2,output:8},documentation:"https://deepseek.ai/models/deepseek-r1"},{id:"deepseek-r1",name:"DeepSeek R1",provider:"DeepSeek",description:"A versatile reasoning-focused foundation model with a 128,000-token context window, designed for comprehensive analytical tasks. It offers strong logical reasoning, consistent output quality, and reliable performance across domains. DeepSeek R1 excels in application areas requiring careful analysis, knowledge synthesis, and complex reasoning, such as research, education, and specialized knowledge work.",category:["Reasoning","General Purpose"],strengths:["Strong reasoning capabilities","Knowledge synthesis","Analytical precision","Consistent outputs"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:1.5,output:6},documentation:"https://deepseek.ai/models/deepseek-r1"},{id:"deepseek-v3-0324",name:"DeepSeek v3-0324",provider:"DeepSeek",description:"A next-generation model from DeepSeek with a 64,000-token context window, featuring enhanced reasoning, multilingual capabilities, and improved instruction following. It delivers advanced performance across domains with particular strength in technical content, code generation, and complex problem-solving while maintaining efficient response generation and processing requirements.",category:["General Purpose"],tags:["new"],strengths:["Enhanced reasoning","Technical expertise","Efficient processing","Multilingual support"],contextSize:"64,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:1.8,output:7.2},documentation:"https://deepseek.ai/models"},{id:"deepseek-r1-qwen-32b",name:"Deepseek R1 Qwen 32B",provider:"DeepSeek",description:"A mid-sized DeepSeek reasoning model with a 128,000-token context window, based on the Qwen architecture. It provides strong logical reasoning and complex task completion with lower computational demands, making it ideal for efficient analytical applications like data interpretation, automated reasoning, and technical problem-solving.",category:["General Purpose"],strengths:["Reasoning capabilities","Efficiency","Instruction following"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.3,output:.9},documentation:"https://github.com/deepseek-ai/DeepSeek-R1"},{id:"open-mistral-nemo",name:"Open Mistral Nemo",provider:"Mistral",description:"An open-source Mistral model with a 32,000-token context window, optimized with NVIDIA NeMo for superior performance and deployment flexibility. It features enhanced efficiency and hardware acceleration, making it suitable for high-performance inference on NVIDIA platforms, ideal for developers and researchers needing customizable, efficient AI solutions.",category:["General Purpose"],strengths:["Open weights","Efficiency","Local deployment"],contextSize:"32,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!1,reasoning:!0,webSearch:!1},pricing:{input:.1,output:.3},documentation:"https://docs.mistral.ai"},{id:"perplexity-llama-3.1-sonar",name:"Perplexity Llama 3.1 Sonar",provider:"Perplexity",description:"A specialized Perplexity model with a 128,000-token context window, built on Llama 3.1 for real-time information retrieval. It integrates web search capabilities and knowledge-intensive training, providing factually accurate responses for applications like research assistance, question answering, and current event analysis.",category:["General Purpose","Information Retrieval"],strengths:["Information retrieval","Web search capabilities","Factual responses"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!0},pricing:{input:.4,output:1.2},documentation:"https://docs.perplexity.ai"},{id:"perplexity-r1-1776",name:"Perplexity R1 1776",provider:"Perplexity",description:"An advanced Perplexity model with a 128,000-token context window, combining strong reasoning with real-time information retrieval. It excels in complex analytical tasks requiring up-to-date data, such as market research, policy analysis, and detailed problem-solving, offering a blend of logical depth and factual accuracy.",category:["General Purpose","Information Retrieval"],strengths:["Advanced reasoning","Information retrieval","Factual responses"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!0},pricing:{input:.6,output:1.8},documentation:"https://docs.perplexity.ai"},{id:"perplexity-sonar",name:"Perplexity Sonar",provider:"Perplexity",description:"Perplexity's flagship model with a 128,000-token context window, featuring industry-leading online search and information synthesis. It provides real-time web access, source attribution, and high factual accuracy, making it ideal for knowledge-intensive applications like academic research, journalism, and real-time decision-making support.",category:["General Purpose","Information Retrieval"],strengths:["Online search","Information retrieval","Factual responses","Real-time information"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!0},pricing:{input:.8,output:2.4},documentation:"https://docs.perplexity.ai"},{id:"qwen-2.5-32b",name:"Qwen 2.5 32B",provider:"Qwen",description:"An advanced multilingual model from Alibaba Cloud with a 128,000-token context window, offering excellent performance across languages and tasks. It features sophisticated reasoning and code generation, making it ideal for global applications like cross-lingual content creation, technical development, and enterprise-grade automation.",category:["General Purpose"],strengths:["Multilingual capabilities","Strong reasoning","Long context handling","Code generation"],contextSize:"128,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.4,output:1.2},documentation:"https://qwen.ai"},{id:"qwen-plus",name:"Qwen Plus",provider:"Qwen",description:"An optimized Qwen model with a 32,000-token context window, enhanced for production-grade applications. It offers strong multilingual support and efficie
1nt processing, tailored for enterprise use cases like customer service automation, multilingual document analysis, and high-throughput workflows requiring reliable performance.",category:["General Purpose"],strengths:["Balanced capabilities","Multilingual support","Instruction following"],contextSize:"32,000 tokens",capabilities:{textGeneration:!0,imageUnderstanding:!1,codeGeneration:!0,functionCalling:!0,reasoning:!0,webSearch:!1},pricing:{input:.2,output:.6},documentation:"https://qwen.ai"}];a.slice(0,6)},37031:(e,i,t)=>{let n;t.d(i,{Button:()=>d});var a=t(88932),o=t(20200),s=t(35238),r=t(85938),l=t(74916);let c=(0,r.F)("inline-flex items-center justify-center gap-2 whitespace-nowrap rounded-md text-sm font-medium ring-offset-background transition-colors focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:pointer-events-none disabled:opacity-50 [&_svg]:pointer-events-none [&_svg]:size-4 [&_svg]:shrink-0",{variants:{variant:{default:"bg-primary text-primary-foreground hover:bg-primary/90",destructive:"bg-destructive text-destructive-foreground hover:bg-destructive/90",outline:"border border-input bg-background hover:bg-accent hover:text-accent-foreground",secondary:"bg-secondary text-secondary-foreground hover:bg-secondary/80",ghost:"hover:bg-accent hover:text-accent-foreground",link:"text-primary underline-offset-4 hover:underline"},size:{default:"h-10 px-4 py-2",sm:"h-9 rounded-md px-3",lg:"h-11 rounded-md px-8",icon:"h-10 w-10"}},defaultVariants:{variant:"default",size:"default"}}),d=(n=o.forwardRef((e,i)=>{let{className:t,variant:n,size:o,asChild:r=!1,...d}=e;if(r&&void 0===s.DX)return console.error("Slot is undefined"),(0,a.jsx)("button",{className:(0,l.cn)(c({variant:n,size:o,className:t})),ref:i,...d});let p=r?s.DX:"button";return(0,a.jsx)(p,{className:(0,l.cn)(c({variant:n,size:o,className:t})),ref:i,...d})}),o.forwardRef((e,i)=>{try{return(0,a.jsx)(n,{...e,ref:i})}catch(e){return console.error("Button component error:",e),null}}));d.displayName="Button"},67787:(e,i,t)=>{t.d(i,{E:()=>r});var n=t(88932);t(20200);var a=t(85938),o=t(74916);let s=(0,a.F)("inline-flex items-center rounded-full border px-2.5 py-0.5 text-xs font-semibold transition-colors focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2",{variants:{variant:{default:"border-transparent bg-primary text-primary-foreground hover:bg-primary/80",secondary:"border-transparent bg-secondary text-secondary-foreground hover:bg-secondary/80",destructive:"border-transparent bg-destructive text-destructive-foreground hover:bg-destructive/80",outline:"text-foreground"}},defaultVariants:{variant:"default"}});function r(e){let{className:i,variant:t,...a}=e;return(0,n.jsx)("div",{className:(0,o.cn)(s({variant:t}),i),...a})}},72437:(e,i,t)=>{t.d(i,{BT:()=>c,Wu:()=>d,ZB:()=>l,Zp:()=>s,aR:()=>r,wL:()=>p});var n=t(88932),a=t(20200),o=t(74916);let s=a.forwardRef((e,i)=>{let{className:t,...a}=e;return(0,n.jsx)("div",{ref:i,className:(0,o.cn)("rounded-lg border bg-card text-card-foreground shadow-sm",t),...a})});s.displayName="Card";let r=a.forwardRef((e,i)=>{let{className:t,...a}=e;return(0,n.jsx)("div",{ref:i,className:(0,o.cn)("flex flex-col space-y-1.5 p-6",t),...a})});r.displayName="CardHeader";let l=a.forwardRef((e,i)=>{let{className:t,...a}=e;return(0,n.jsx)("div",{ref:i,className:(0,o.cn)("text-2xl font-semibold leading-none tracking-tight",t),...a})});l.displayName="CardTitle";let c=a.forwardRef((e,i)=>{let{className:t,...a}=e;return(0,n.jsx)("div",{ref:i,className:(0,o.cn)("text-sm text-muted-foreground",t),...a})});c.displayName="CardDescription";let d=a.forwardRef((e,i)=>{let{className:t,...a}=e;return(0,n.jsx)("div",{ref:i,className:(0,o.cn)("p-6 pt-0",t),...a})});d.displayName="CardContent";let p=a.forwardRef((e,i)=>{let{className:t,...a}=e;return(0,n.jsx)("div",{ref:i,className:(0,o.cn)("flex items-center p-6 pt-0",t),...a})});p.displayName="CardFooter"},74916:(e,i,t)=>{t.d(i,{cn:()=>r});var n=t(54624),a=t(32613);let o=function(){for(var e=arguments.length,i=Array(e),t=0;t<e;t++)i[t]=arguments[t];try{return(0,n.$)(...i)}catch(e){return console.error("Error in clsx:",e),""}},s=e=>{try{return(0,a.QP)(e)}catch(i){return console.error("Error in twMerge:",i),e}};function r(){for(var e=arguments.length,i=Array(e),t=0;t<e;t++)i[t]=arguments[t];
1try{let e=i.filter(Boolean),t=o(...e);return"string"==typeof t?s(t):""}catch(e){return console.error("Error in cn utility:",e),""}}}}]);
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.