GPT-5.6 Sol vs Kimi K3

head-to-head

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 93.4% for Kimi K3, a 2.8-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?

Kimi K3 is the cheaper model: $3 per 1M input tokens ($15 output) versus $5 ($30 output) for GPT-5.6 Sol — roughly 1.7× 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.

Kimi K3 ships open weights. Beyond the per-token discount, that means you can self-host it, fine-tune it, pin a snapshot so the model can't change under you, and keep code on your own infrastructure — none of which is possible with GPT-5.6 Sol, which is API-only. For teams with compliance constraints that difference outweighs any benchmark point.

when to pick each

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.
• Kimi K3: Independent (vals.ai, mini-swe-agent bash-only harness): SWE-bench Verified 93.40% ±1.11. Verified Jul 18, 2026 — vals.ai had not run K3 at our Jul 17 check and now ranks it third overall (above GPT-5.6 Luna at 93.0% and Claude Opus 4.8 at 88.6%), making it the highest-scoring open-weight coder we track. Moonshot published no SWE-bench Verified score of its own, only Terminal-Bench 2.1 88.3% on its KimiCode harness, so we rank on the independent number per our standing rule. Also 3rd on Artificial Analysis GDPval-AA v2 and 2nd on AA-Briefcase. Price: Moonshot API $3/$15 per 1M (cache-hit input $0.30); open weights promised Jul 27, 2026.

Full reviewsGPT-5.6 Sol, decodedKimi K3, decoded

Ranked on our AI Coding Leaderboard, updated 2026-07-18. Scores are confirmed against primary sources; prices are per 1M input tokens and can change.