Choose this when
You are comparing providers, migrating models, routing tasks, or balancing cost, speed, context, and quality.
All learning paths
AI learning path
Frontier models and model selection
Choose models with evidence instead of leaderboard screenshots and social-media vibes.
- Best for
- Builders choosing between Claude, GPT, Gemini, Llama, Mistral, Cohere, DeepSeek, Qwen, Grok, Perplexity, and hosted open models
- Level
- Intermediate
- Time
- 6-12 hours
You should be able to
You can build a small model-selection matrix and test candidates against your own tasks.
Checkpoint
Move on when you can justify model choice by task evidence, not brand preference.
Do
Learning sequence
Work through the material inside each step. Videos are embedded where they fit; tutorials and references sit next to the task they support.
Step 1
Define the job
Separate coding, extraction, chat, multimodal, long-context, search, and agent tasks.
Watch here
►
The last six months in LLMs in five minutes
Use this for current model landscape orientation before comparing docs.
Open here
OpenAI model guide
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.
Open resourceStep 2
Compare primary docs
Read official model docs for context, modalities, tool support, pricing, and deprecations.
Open here
Claude choosing a model
You need Anthropic's current guidance on balancing capability, speed, and cost before changing Claude models.
Open resourceStep 3
Run your own eval
Test candidate models on real examples before routing or migrating production workflows.
Watch here
►
Open Challenges for AI Engineering
Good context for model tradeoffs, migrations, and evidence-based selection.
Open here
Gemini API models
You need to compare current Gemini stable, preview, latest, and experimental model IDs, context windows, and modality support.
Open resourceOpenRouter models guide
You need to compare many model families through one catalog before testing prompts across providers.
Open resourceSimon Willison: The last six months in LLMs in five minutes
You want a grounded tour of current LLM tooling, model tradeoffs, and the practical ecosystem.
Open resourcePractice task
Build a five-row comparison table for two or three models using your own prompts, not generic benchmarks.
Reference
All resources in this path
Step 1
OpenAI model guide
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.
Step 2
Claude choosing a model
You need Anthropic's current guidance on balancing capability, speed, and cost before changing Claude models.
Step 3
Gemini API models
You need to compare current Gemini stable, preview, latest, and experimental model IDs, context windows, and modality support.
Step 3
OpenRouter models guide
You need to compare many model families through one catalog before testing prompts across providers.
Step 3
Simon Willison: The last six months in LLMs in five minutes
You want a grounded tour of current LLM tooling, model tradeoffs, and the practical ecosystem.
Educators to follow
Simon Willison
Beginner to advanced
Read the recent model-roundup posts, then try the llm command-line tool with two or three different providers.
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Swyx
Intermediate to advanced
Watch AI Engineer talks for production patterns and tool choices.
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Josh Pigford
Beginner to intermediate
Read the public notes and examples before deciding whether the paid material matches your business.
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Brian Casel
Beginner to intermediate
Look for workflow breakdowns and implementation examples.
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Peter Yang
Intermediate
Review the Maven syllabus and compare it to your current product workflow.
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Lenny Rachitsky
Beginner to intermediate
Browse the How I AI interviews and copy the workflows that match your role.
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