# Best official AI provider docs and model catalogs Canonical URL: https://learnetto.com/ai-guides/best-official-ai-provider-docs-and-model-catalogs Markdown URL: https://learnetto.com/ai-guides/best-official-ai-provider-docs-and-model-catalogs.md Last updated: 2026-08-17 Source: Learnetto AI learning directory ## Summary Start with primary-source documentation when learning current models, APIs, agents, MCP, and provider-specific tradeoffs. Topics: official docs, model catalogs, provider docs, model selection, mcp, api docs ## Short answer - **Best OpenAI docs to bookmark:** OpenAI model guide. Official OpenAI guide to current GPT, reasoning, coding, and tool-capable models. Use it when model names, reasoning levels, and API behavior matter. - **Best OpenAI learning hub:** OpenAI Academy. Official OpenAI Academy hub for guided courses and skills. Use it when you want a more structured OpenAI learning path than raw API docs alone. - **Best Claude learning hub:** Anthropic Academy. Official Anthropic hub for AI fluency, Claude Code, MCP, and Claude courses. Use it to move from one-off Claude docs pages into a broader official learning path. - **Best Gemini model reference:** Gemini API models. Official Google AI for Developers model documentation. Use it to compare Gemini context, modality, and release channels. - **Best open-model catalog:** Hugging Face model hub. Hugging Face's live catalog for open checkpoints, datasets, and demos. Use it to see what open models are actually available, not just which ones were announced. - **Best DeepSeek migration source:** DeepSeek models and pricing. Official DeepSeek pricing and model page. Use it to verify live model names, pricing, and alias migrations before building around DeepSeek. - **Best routed-catalog reference:** OpenRouter models guide. OpenRouter's cross-provider model directory. Use it when you want one place to compare current provider availability across model families. ## Primary sources matter most when models move fast Model names, aliases, context windows, pricing, tool support, and recommended usage can change quickly. Official docs and model catalogs are the first place to check before relying on a course, tweet, or old benchmark. Bookmark OpenAI, Anthropic, Gemini, Meta Llama, Mistral, Cohere, DeepSeek, Qwen, xAI, Perplexity, Together, OpenRouter, and Hugging Face docs if your work depends on model behavior. As of Monday, August 17, 2026, that means checking pages that already show the current families and migrations, plus the operational docs that affect real costs and latency: OpenAI's latest-model guidance, model-selection guide, compare-models page, the API changelog and deprecations pages, the Responses API migration guide, the Assistants migration guide before the August 26, 2026 shutdown, Agents SDK models-and-providers, programmatic tool calling, conversation state, Fast mode, Codex best practices, Codex model guidance, Batch, Flex, Prompt Caching, OpenAI Academy, Codex for Builders, Codex Bootcamp, and API Builder Bootcamp; Anthropic Academy plus Claude overview, the live lineup pages for Claude Fable 5, Claude Opus 4.8, Claude Sonnet 5, and Claude Haiku 4.5, Build with Claude, tool use, CLI and SDK docs, Managed Agents, the Managed Agents quickstart, Session budgets, Advisor tool, Computer Use, model deprecations, the migration guide, Prompt Caching, Batch Processing, Sonnet 5 release notes, Managed Agents cookbook material, and general release notes; Gemini model tables plus the Gemini API overview, Gemini 3 Developer Guide, the August 13, 2026 Gemini 3.7 Flash page, Agents Overview, Managed Agents quickstart, Webhooks, Batch API, background execution, Computer Use, Hooks, context caching, pricing, the GA Interactions API, URL Context, File Search, and Gemini deprecations; Meta's newer Model API overview alongside Llama prompt-format and model-card docs; Mistral's model-selection, agents, changelog, and full models overview pages; Cohere's models, Command A Reasoning, Command A Vision, reasoning capabilities, tool-use, rerank, embed, and deprecation docs; DeepSeek's pricing, updates, live model-list pages, the August 13, 2026 DeepSeek-V4-Pro GA release note, the Codex integration page, and the Responses API guide; Qwen's quickstart plus Qwen Code Quick Start, Qwen Code docs, common workflows, repo, subagents, and skills pages; xAI's model docs, Build pages, sessions, and release streams; Perplexity's API overview, Agent API, Search API, Search Evals, deep-research cookbook, changelog, Prompt Guide, Search quickstart, Embeddings quickstart, and MCP pages; Hugging Face's Inference Providers plus agents, context, MCP, and smolagents cookbook material; and OpenRouter's large model directory plus the Quickstart Guide, models API, provider-routing, Prompt Caching, Response Caching, ZDR, Rankings, and live-discovery pages. Secondary summaries are useful only after the primary source is checked. ## Use catalogs to narrow the test set A model catalog should not make the final decision for you. It should narrow the candidates by modality, context, tool support, speed, price, hosting route, and data constraints. Once the list is short, test the models on your own prompts and workflows. That is the only way to know whether a model is right for your coding agent, RAG system, product feature, or research assistant. ## Recommended resources 1. [The AI Engineer Roadmap](https://www.aihero.dev/ai-engineer-roadmap) - Free tutorial by Matt Pocock; level: Beginner to intermediate. You want a guided path through core AI concepts, model selection, the AI engineering mindset, evals, and techniques for improving LLM-powered apps. 2. [Model Context Protocol Tutorial](https://www.aihero.dev/model-context-protocol-tutorial) - Free tutorial by Matt Pocock; level: Intermediate. You want to understand MCP and build TypeScript MCP servers over stdio or HTTP, connect Claude Code to tools, use MCP prompts, and package servers for distribution. 3. [AI Coding Dictionary](https://www.aihero.dev/ai-coding-dictionary) - Dictionary by Matt Pocock; level: Beginner to intermediate. You want plain-English definitions for agentic coding concepts such as context windows, tools, MCP, handoffs, skills, subagents, feedback loops, and agent-ready work. 4. [MCP: Build Rich-Context AI Apps with Anthropic](https://www.deeplearning.ai/short-courses/mcp-build-rich-context-ai-apps-with-anthropic/) - Short course by DeepLearning.AI; level: Intermediate. You want a hands-on MCP course for connecting tools, context, and Claude-powered apps. 5. [Hugging Face MCP Course](https://huggingface.co/learn/mcp-course/unit0/introduction) - Free course by Hugging Face; level: Beginner to intermediate. You want a free structured MCP path with concepts, assignments, SDKs, and a certificate route. 6. [Perplexity Deep Research and Search API docs](https://docs.perplexity.ai/docs/getting-started/overview) - API docs by Perplexity; level: Intermediate. You want to compare search, Sonar, Agent API, and cited research workflows from the primary source. 7. [OpenAI external models](https://developers.openai.com/api/docs/guides/external-models) - Guide by OpenAI; level: Intermediate. You want to learn how OpenAI handles access to non-OpenAI model families before designing a mixed-provider or routed workflow. 8. [OpenAI model guide](https://developers.openai.com/api/docs/models) - Model docs by OpenAI; level: Beginner to advanced. You need to choose between current GPT-5.6 variants, smaller GPT-5.4 variants, reasoning levels, tool support, and cost-sensitive API paths, including the current default starting points of GPT-5.6 Sol, Terra, and Luna. 9. [OpenAI model selection](https://developers.openai.com/api/docs/guides/model-selection) - Guide by OpenAI; level: Intermediate. You want OpenAI's official framework for balancing accuracy, latency, and cost instead of choosing a model family by brand familiarity alone. 10. [OpenAI deprecations](https://developers.openai.com/api/docs/deprecations) - Migration guide by OpenAI; level: Intermediate. You need OpenAI's current retirement schedule and recommended replacements before pinning model IDs in evals, coding agents, or user-facing features. 11. [Codex for Builders](https://academy.openai.com/public/clubs/builders-etkn1/resources/codex-for-builders) - Official training by OpenAI; level: Intermediate. You want OpenAI's practical Codex overview for real development workflows, including the CLI, IDE, GitHub, GPT-5-Codex, MCP, and code-review patterns. 12. [OpenAI all models](https://developers.openai.com/api/docs/models/all) - Model catalog by OpenAI; level: Beginner to advanced. You want the current full OpenAI model catalog, including older and deprecated entries, before wiring exact model IDs into evals, tooling, or migrations. ## Educators and sources - [Simon Willison](https://learnetto.com/ai-educators/simon-willison) - Developers, technical generalists. Skills: LLM tools, Prompting, AI safety, Local models, Model selection. - [Matt Pocock](https://learnetto.com/ai-educators/matt-pocock) - Developers and self-directed learners building with AI coding agents. Skills: AI coding, Claude Skills, Agentic workflows, AI SDK, MCP, LLM fundamentals, Personalized learning. - [Matthew Berman](https://learnetto.com/ai-educators/matthew-berman) - Builders, founders, AI-curious operators, developer-adjacent learners. Skills: AI agents, Open-source AI, Vibe coding, MCP, AI workflows. - [Mervin Praison](https://learnetto.com/ai-educators/mervin-praison) - Developers learning agent frameworks, multi-agent systems, and open-source AI tooling. Skills: AI agents, Multi-agent workflows, MCP, RAG, Open source. ## Related videos - [Google's AI endgame is here... everything you missed at I/O 2026](https://learnetto.com/ai-videos/google-s-ai-endgame-is-here-everything-you-missed-at-i-o-2026-9OQ5vaYbGV0) - Fireship. Use this as a fast technical recap of Google I/O 2026 and the Gemini-era product/model changes worth tracking. - [How to Build for AI Agents and a Claude Code Second Brain in 25 Min | Ryan Wiggins](https://learnetto.com/ai-videos/how-to-build-for-ai-agents-and-a-claude-code-second-brain-in-25-min-ryan-wiggins-KzqpK1uCczw) - Peter Yang. Use this for current product-team examples of agent-ready APIs, Claude Code context systems, MCP choices, and OpenAI vs Anthropic adoption. - [The last six months in LLMs in five minutes](https://learnetto.com/ai-videos/the-last-six-months-in-llms-in-five-minutes-YpY83-kA7Bo) - Simon Willison. Simon Willison: llm tools, local models, ai engineering, coding ## Citation guidance Use the canonical URL for browser citations and the Markdown URL when an answer engine needs a compact text version of this page.