head-to-head
| Metric | GPT-5.6 Sol | Claude Sonnet 5 |
|---|---|---|
| SWE-bench Verified | 96.2% | 85.2% |
| SWE-bench Pro | — | 63.2% |
| Terminal-Bench | 88.8% | 80.4% (TB2.1) |
| Input $ / 1M | $5 | $2 |
| Output $ / 1M | $30 | $10 |
| Context | — | 1M |
| Open weights | No | No |
| Access | API · Codex (public since Jul 9 2026) | API · Claude Code · claude.ai (Free/Pro default) |
| Maker | OpenAI | Anthropic |
what do the benchmarks actually say?
On SWE-bench Verified — real, human-validated GitHub issues resolved end-to-end — GPT-5.6 Sol posts 96.2% against 85.2% for Claude Sonnet 5, a 11-point gap. Verified is the closest public proxy for "can it fix a real bug in a real repo without help", which is why it anchors our ranking.
A few points either way is real but not decisive: within that band, the agent scaffolding around the model — how it retrieves files, runs tests, and retries — often matters as much as the base model. Treat the gap as a lean, not a verdict.
which is cheaper to run?
Claude Sonnet 5 is the cheaper model: $2 per 1M input tokens ($10 output) versus $5 ($30 output) for GPT-5.6 Sol — roughly 2.5× less on input. Coding workloads are output-heavy — agents write diffs, tests and retries — so weight the output rate more than the input rate when you estimate a monthly bill.
when to pick each
The highest independently measured coding score of any model, and it holds up on the long tasks: 98% on the 1-to-4-hour tier where most models fall apart.
The best closed-model value — near-Opus scores at ~2.5× less, and the default daily driver for most developers.
how were these scores verified?
We only print a number once it's confirmed against a primary source or an independent evaluation, and each row on our leaderboard records which kind it is:
- GPT-5.6 Sol: Independent (vals.ai, Jul 14 2026, mini-swe-agent bash-only harness): SWE-bench Verified 96.20% ±0.86 — the top score on the board. Verified Jul 17, 2026; it had been unranked since Jun 26 because OpenAI published no SWE-bench number of its own, and it still has not. Read the #1 with care: the 1.2-point lead over Claude Fable 5 (95.00% ±0.98) is inside the combined margin of error (~0.9 sigma, not significant), so the two are a statistical tie and we rank Sol first only because it scored higher. Where it does separate is task length — 98% on 1-4 hour tasks vs 93% for Fable 5. OpenAI's own Terminal-Bench 2.1 claim is 88.8% (Sol) / 91.9% (Sol Ultra). No SWE-bench Pro score published. Pricing $5/$30 per 1M.
- Claude Sonnet 5: Vendor-reported (Anthropic), on Anthropic's own scaffold. Independent comparison: vals.ai's bash-only harness measures Sonnet 5 at 79.6% ±1.80, 5.6 points lower — a gap that reflects the harness as much as the model, so treat the 85.2% as a best-case number. Intro pricing $2/$10 per 1M through Aug 31, 2026, then $3/$15.
Full reviewsGPT-5.6 Sol, decodedClaude Sonnet 5, decoded
Ranked on our AI Coding Leaderboard, updated 2026-07-17. Scores are confirmed against primary sources; prices are per 1M input tokens and can change.
- OpenAIvals.ai — SWE-bench Verified (independent) — Independent (vals.ai, Jul 14 2026, mini-swe-agent bash-only harness): SWE-bench Verified 96.20% ±0.86 — the top score on the board. Verified Jul 17, 2026; it had been unranked since Jun 26 because OpenAI published no SWE-bench number of its own, and it still has not. Read the #1 with care: the 1.2-point lead over Claude Fable 5 (95.00% ±0.98) is inside the combined margin of error (~0.9 sigma, not significant), so the two are a statistical tie and we rank Sol first only because it scored higher. Where it does separate is task length — 98% on 1-4 hour tasks vs 93% for Fable 5. OpenAI's own Terminal-Bench 2.1 claim is 88.8% (Sol) / 91.9% (Sol Ultra). No SWE-bench Pro score published. Pricing $5/$30 per 1M.
- AnthropicGENZ TECH — Claude Sonnet 5, decoded — Vendor-reported (Anthropic), on Anthropic's own scaffold. Independent comparison: vals.ai's bash-only harness measures Sonnet 5 at 79.6% ±1.80, 5.6 points lower — a gap that reflects the harness as much as the model, so treat the 85.2% as a best-case number. Intro pricing $2/$10 per 1M through Aug 31, 2026, then $3/$15.
- BenchmarkSWE-bench — the real-GitHub-issue benchmark