The best coding models in 2026: a hands-on comparison
How to pick a coding model by the job — frontier vs agentic-mid vs fast — measured on cost per merged PR, not cost per token.
The fastest way to feel the difference between coding models is to give them the same repo task and read the diffs. That is exactly what app.nz agents do — and what the Model Comparison tool lets you do interactively. This post is the cheat-sheet we reach for when picking a default.
How we think about coding models
A "coding model" is judged on four axes that matter in practice, not on a single leaderboard number:
- Instruction adherence — does it stay inside the diff you asked for, or rewrite the world?
- Long-context reasoning — can it hold a multi-file change in its head and keep edits consistent?
- Tool use — does it reliably call tools (run tests, read files) in an agent loop?
- Cost per solved task, not cost per token — a pricier model that one-shots a fix is often cheaper end to end.
The shortlist
| Tier | Good default for | Strengths | Watch-outs |
|---|---|---|---|
| Frontier | Hard multi-file changes, refactors, migrations | Best reasoning + tool use, fewest retries | Highest per-token cost |
| Agentic mid | Day-to-day PRs, CI repair | Strong adherence at lower cost | Occasionally needs a nudge on big refactors |
| Fast / cheap | Boilerplate, lint fixes, codemods | Very low latency + cost | Weaker on ambiguous specs |
On app.nz you don't pin one model and hope. The app/auto-code route picks a best-fit model per task, and you can always override per request.
Pick by the job, not the brand
- Greenfield feature in a small repo — a fast model is usually enough; save frontier budget for the gnarly stuff.
- Refactor across 10+ files — go frontier. The retry savings dwarf the token premium.
- "Fix the failing test" — agentic mid models shine; they read the trace, edit, and re-run.
Rule of thumb: measure cost per merged PR, not cost per million tokens. A model that needs three attempts is not cheap.
Prove it on your own code
Talk is cheap — run the comparison:
- Send one prompt to several models side by side with the Model Comparison tool.
- Score outputs on your rubric in bulk with Bulk Evals.
- Auto-tune the prompt you feed them with the Prompt Optimizer.
- Hand the winner a real repo task in Coding Agent.
Live prices for every model are on the gateway, and you can estimate a request's cost before you send it with the Token & Cost Estimator.