Decision tool

AI Model Picker

Stop reading 20 leaderboard pages. Tell us the workflow, budget, context needs, and risk profile. Get a practical model shortlist with a cost-aware recommendation.

Data verified: 2026-08-0320 models in selector

What are you building?

Shortlist

Decision scores are relative to your selections and rank this shortlist. They are not benchmark scores on a 10-point scale. Review sources and methodology.

#1 GPT-5.6 SolOpenAI

Complex production workflows • Coding • Multi-agent orchestration

Decision score 9.7 • $5/$30 per 1M
#2 GPT-5.4OpenAI

Coding • Agents • Tool integration

Decision score 9.6 • $2.5/$15 per 1M
#3 GPT-5.6 TerraOpenAI

Production agents • Coding • Cost-balanced workflows

Decision score 9.6 • $2/$12 per 1M
#4 Claude Opus 4.8Anthropic

Complex reasoning • Agentic coding • Enterprise work

Decision score 9.6 • $5/$25 per 1M
#5 GPT-5.5OpenAI

Complex reasoning • Coding • Professional workflows

Decision score 9.5 • $5/$30 per 1M

Before you decide

AI model picker FAQ

How does the AI Model Picker choose a recommendation?

The picker weights normalized coding, reasoning, tool-use, context-window, and price signals against the workflow and constraints you select. It is a directional decision aid, not a substitute for evaluating models on your own production tasks.

Which AI model is best for coding or agent workflows?

The best choice depends on the coding task, tool-calling requirements, context size, budget, and deployment constraints. Select Coding or Agent workflows in the picker to see a ranked shortlist based on those priorities, then validate the finalists with representative tasks.

How should I compare AI model costs?

Compare both input and output token prices using your expected traffic and response lengths. The picker shows listed per-million-token pricing, and the cost calculator can estimate a workload before you commit to a model.

Can I use the picker for local or private AI deployment?

Yes. Choose Local / private deployment or Prefer local / open weights to prioritize models suited to self-hosted workflows. Confirm hardware, licensing, throughput, and security requirements before deployment.