head-to-head
| Metric | Kimi K3 | Grok 4.5 |
|---|---|---|
| SWE-bench Verified | 93.4% | 86.6% |
| SWE-bench Pro | — | 64.7% |
| Terminal-Bench | 88.3% | 83.3% (TB2.1) |
| Input $ / 1M | $3 | $2 |
| Output $ / 1M | $15 | $6 |
| Context | 1M | — |
| Open weights | Yes | No |
| Access | API · app · open weights promised Jul 27, 2026 | API · SpaceXAI console · Grok Build · Cursor (all plans); not in EU yet |
| Maker | Moonshot AI | SpaceXAI (xAI) |
what do the benchmarks actually say?
On SWE-bench Verified — real, human-validated GitHub issues resolved end-to-end — Kimi K3 posts 93.4% against 86.6% for Grok 4.5, a 6.8-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?
Grok 4.5 is the cheaper model: $2 per 1M input tokens ($6 output) versus $3 ($15 output) for Kimi K3 — roughly 1.5× 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.
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 Grok 4.5, which is API-only. For teams with compliance constraints that difference outweighs any benchmark point.
when to pick each
The highest-scoring open-weight model on the board and the largest ever announced (2.8T MoE, 16 of 896 experts active): frontier-adjacent coding you can eventually self-host, at a third of Fable 5's price.
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:
- 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.
- 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 reviewsKimi K3, decodedGrok 4.5, 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.
- Moonshot AIvals.ai — SWE-bench Verified (independent) — 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.
- 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