Best official AI provider docs and model catalogs

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, Llama, Mistral, Cohere, DeepSeek, Qwen, xAI, Perplexity, Together, OpenRouter, and Hugging Face docs if your work depends on model behavior. As of Monday, July 27, 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 plus compare-models, the Responses API migration guide, conversation state, Codex best practices, Batch, Flex, Prompt Caching, the Agent Builder deprecation notice, and OpenAI Academy; Anthropic Academy plus Claude overview, the current Claude lineup, Managed Agents, Advisor tool, Prompt Caching, Batch Processing, and release notes; Gemini model tables plus the Gemini 3 Developer Guide, Agents Overview, Batch API, background execution, Computer Use, Hooks, context caching, pricing, the GA Interactions API, URL Context, File Search, and deprecations in Google's docs; Mistral's model-selection and changelog pages; Cohere's models, rerank, and embed docs; DeepSeek's pricing and updates pages; and OpenRouter's large model directory plus provider-routing and Fusion Router docs. Secondary summaries are useful only after the primary source is checked.

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.