head-to-head
| Metric | GPT-5.6 Sol | Grok 4.5 |
|---|---|---|
| SWE-bench Verified | 96.2% | 86.6% |
| SWE-bench Pro | — | 64.7% |
| Terminal-Bench | 88.8% | 83.3% (TB2.1) |
| Input $ / 1M | $5 | $2 |
| Output $ / 1M | $30 | $6 |
| Context | — | — |
| Open weights | No | No |
| Access | API · Codex (public since Jul 9 2026) | API · SpaceXAI console · Grok Build · Cursor (all plans); not in EU yet |
| Maker | OpenAI | SpaceXAI (xAI) |
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 86.6% for Grok 4.5, a 9.6-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?
Grok 4.5 is the cheaper model: $2 per 1M input tokens ($6 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 value at the top of the board: it solves a SWE-bench Verified task for about $2.31 of input, less than half what the two models above it cost, and it is the fastest of the leaders.
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.
- Grok 4.5: Independent (vals.ai, Jul 14 2026, mini-swe-agent bash-only harness): SWE-bench Verified 86.6% ±1.52. Verified Jul 17, 2026 — it launched Jul 8 with no Verified score and we had it unranked as "Opus-class, unproven"; the independent number now backs the Opus-class claim, landing it 2 points under Claude Opus 4.8 at 40% of the input price. On our price-per-solved-task metric that is ~$2.31 against $5.64 for Opus 4.8 and $10.53 for Fable 5, the cheapest of any model scoring above 85%. It is also quick: 199.6s mean latency per task versus 566.9s for Opus 4.8. SWE-bench Pro 64.7% and Terminal-Bench 2.1 83.3% remain SpaceXAI-reported. Priced $2/$6 per 1M. Still not available in the EU.
Full reviewsGPT-5.6 Sol, decodedGrok 4.5, 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.
- SpaceXAI (xAI)vals.ai — SWE-bench Verified (independent) — Independent (vals.ai, Jul 14 2026, mini-swe-agent bash-only harness): SWE-bench Verified 86.6% ±1.52. Verified Jul 17, 2026 — it launched Jul 8 with no Verified score and we had it unranked as "Opus-class, unproven"; the independent number now backs the Opus-class claim, landing it 2 points under Claude Opus 4.8 at 40% of the input price. On our price-per-solved-task metric that is ~$2.31 against $5.64 for Opus 4.8 and $10.53 for Fable 5, the cheapest of any model scoring above 85%. It is also quick: 199.6s mean latency per task versus 566.9s for Opus 4.8. SWE-bench Pro 64.7% and Terminal-Bench 2.1 83.3% remain SpaceXAI-reported. Priced $2/$6 per 1M. Still not available in the EU.
- BenchmarkSWE-bench — the real-GitHub-issue benchmark