# Best AI resources for frontier model selection Canonical URL: https://learnetto.com/ai-guides/best-ai-resources-for-frontier-model-selection Markdown URL: https://learnetto.com/ai-guides/best-ai-resources-for-frontier-model-selection.md Last updated: 2026-06-23 Source: Learnetto AI learning directory ## Summary Choose between GPT, Claude, Gemini, Llama, Mistral, Cohere, DeepSeek, Qwen, Grok, Perplexity, and routed model catalogs without guessing. Topics: frontier models, model selection, gpt-5.5, claude fable, gemini, openrouter ## Short answer - **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 models page centers Claude Fable 5 for widely released high-end work, Gemini's model page spans 2.5 Pro, 2.5 Flash-Lite, and 3.1 Flash Live Preview, 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 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. [OpenAI model guide](https://developers.openai.com/api/docs/models) - Model docs by OpenAI; level: Beginner to advanced. You need to choose between GPT-5.5, GPT-5.5 Pro, GPT-5.4 mini, GPT-5.4 nano, reasoning levels, tool support, and cost-sensitive API paths. 3. [Using GPT-5.5](https://developers.openai.com/api/docs/guides/latest-model) - Guide by OpenAI; level: Intermediate. You need the current OpenAI guidance for migrating to GPT-5.5, prompt shape changes, and tool-heavy workflow behavior. 4. [GPT-5.5 prompting guide](https://developers.openai.com/api/docs/guides/prompt-guidance) - Guide by OpenAI; level: Intermediate. You want the official prompting adjustments for GPT-5.5 instead of reusing older GPT-4 or GPT-5 prompt habits unchanged. 5. [OpenAI reasoning model guide](https://developers.openai.com/api/docs/guides/reasoning) - Guide by OpenAI; level: Intermediate. You need to understand when internal reasoning is useful for coding, scientific work, agents, and harder multi-step tasks. 6. [Claude models overview](https://docs.anthropic.com/en/docs/about-claude/models) - Model docs by Anthropic; level: Beginner to advanced. You need the official comparison of current Claude models, context windows, aliases, and release families before choosing cost, speed, and reliability tradeoffs. 7. [Gemini API models](https://ai.google.dev/gemini-api/docs/models) - Model docs by Google AI for Developers; level: Beginner to advanced. You need to compare current Gemini stable, preview, latest, and experimental model IDs, context windows, and modality support. 8. [Gemini coding agent setup](https://ai.google.dev/gemini-api/docs/coding-agents) - Guide by Google AI for Developers; level: Intermediate. You want Google's official setup path for Gemini-driven coding-agent workflows, Gemini Docs MCP, and skills rather than generic prompt advice. 9. [Gemini Agents Overview](https://ai.google.dev/gemini-api/docs/agents) - Guide by Google AI for Developers; level: Intermediate. You want the official overview of Gemini managed agents, sandbox behavior, and when to use agent workflows instead of plain model calls. 10. [Gemini API changelog](https://ai.google.dev/gemini-api/docs/changelog) - Release notes by Google AI for Developers; level: Intermediate. You need the official Gemini launch and shutdown timeline before relying on preview model IDs or older Flash variants. 11. [Gemini Live API overview](https://ai.google.dev/gemini-api/docs/live-api) - Guide by Google AI for Developers; level: Intermediate. You want the official Google path for low-latency voice and vision agents before designing a realtime Gemini workflow. 12. [Llama API model endpoint](https://llama.developer.meta.com/docs/api/models/) - API reference by Meta Llama; level: Intermediate. You need the machine-readable Llama API models endpoint and specifications before wiring model discovery into tooling or eval configs. ## 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. - [Hands-on Agentic AI for Leaders](https://learnetto.com/ai-educators/hands-on-agentic-ai-for-leaders) - Leaders, executives, managers. Skills: Agentic AI, AI assistants, Leadership workflows, Prompt refinement. ## Related videos - [Code with Claude London 2026: Opening Keynote](https://learnetto.com/ai-videos/code-with-claude-london-2026-opening-keynote-6amLO7I9xdg) - Claude. Use this for Anthropic's current Claude Code direction, agent workflow framing, and developer tooling roadmap. - [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.