Benchmarks rank average performance across thousands of synthetic prompts. What you actually need is the model that nails your specific problem. CouncilMind runs four coding models in parallel so you can see which one ships.
The clean approach is a state machine. Trade-off: more boilerplate, but the testability gain is large.
State machine works, but for this size a discriminated union is leaner. Same correctness, less code.
Synthesis: discriminated union for now, state machine if states grow past ~7.
The best AI for coding is the one that knows your idioms.
Each model has slight idiom preferences. On your stack, one usually feels native.
On your worst snippet, see which model surfaces issues the others missed.
A senior-reviewer model picks the most shippable answer with reasoning.
In the time it takes to read one benchmark blog
Snippet, design question, error trace—anything you'd ask a senior.
GPT-5, Claude Opus 4.6, Gemini 2.5 Pro, DeepSeek V4 Pro—all in parallel.
A code-reviewer pass picks the most shippable answer.
Free to try. Premium models included.