Best OpenAI primary source: OpenAI compare models. Official OpenAI model comparison page. Use it before swapping OpenAI models in coding, agent, or product workflows.
Best Claude primary source: Claude choosing a model. Official Anthropic model-selection guidance. Use it to compare speed, capability, and cost across Claude model families.
Best multi-provider catalog: OpenRouter models guide. OpenRouter catalog for comparing model families across providers. Use it when you need a broad view before testing prompts yourself.
Model selection needs tests, not vibes
Frontier model comparisons change constantly, and generic leaderboards rarely match your product. The right process is to start with official model docs, choose two or three candidates, and test them on your actual tasks.
Right now the official docs are especially useful because they surface concrete shifts: OpenAI points new users to GPT-5.5 for complex reasoning and coding, Anthropic's docs pair the current Claude family with release notes, Gemini's docs now span current model tables plus Interactions, Deep Research, 3.5 Flash guidance, and deprecations, and DeepSeek's pricing page spells out the migration from `deepseek-chat` and `deepseek-reasoner` aliases to DeepSeek V4 Flash modes. Start there, then run your own evals for quality, latency, cost, tool use, structured output, and failure behavior.
Do not migrate because a model is famous
A stronger model on paper can be worse for a workflow if it is slower, more expensive, weaker at structured output, less reliable with tools, or harder to operate within your system. Model choice is an engineering and product decision.
The best resources for this topic are primary sources and repeatable tests. Blog posts and screenshots can be useful for discovery, but production migration should depend on current docs and your own task set.
Recommended courses and resources
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