Model comparison
GPT-6 Sol vs Kimi K2 (Jul 2025)
GPT-6 Sol is the stronger model overall, scoring 61.8 to 41.2 on the Noometry Index. Kimi K2 (Jul 2025) costs 4.0× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. GPT-6 Sol scores higher in 9 categories and Kimi K2 (Jul 2025) in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Sol leads 74.0 to 23.3.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 6.5% for GPT-6 Sol and 17.9% for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) is cheaper at $0.57 / $2.30 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 262K.
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Sol | Kimi K2 (Jul 2025) | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 61.8 | 41.2 |
| Released | 2026-09-22 | 2025-07-12 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $2 | $0.57 |
| Output $ / M tokens | $10 | $2.30 |
| Results tracked | 45 | 42 |
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Category by category
Coding GPT-6 Sol leads
GPT-6 Sol: 60.1 (#11), Kimi K2 (Jul 2025): 42.4 (#102)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Coding | 1447 | 1399 |
| ALE-Bench | 2,462 | 597.5 |
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| SWE-bench Verified (bash only) | — | 63.4% |
| Aider Polyglot | — | 59.1% |
| LMArena WebDev | 1688 | — |
| SciCode | 57.6% | — |
| GSO | — | 4.9% |
| WeirdML | — | 42.8% |
Agentic & Tool Use GPT-6 Sol leads
GPT-6 Sol: 37.2 (#36), Kimi K2 (Jul 2025): 32.4 (#64)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| Terminal-Bench | — | 35.7% |
| APEX-Agents | 54.3% | — |
| Berkeley Function Calling Leaderboard | — | 59.1% |
| GDP.pdf | 26.4% | — |
| METR Time Horizons | — | 59.2% |
| Vending-Bench 2 | 14,428 | — |
Reasoning GPT-6 Sol leads
GPT-6 Sol: 74.0 (#9), Kimi K2 (Jul 2025): 23.3 (#179)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Hard Prompts | 1418 | 1384 |
| Epoch Capabilities Index | 162.72 | 146.01 |
| ARC-AGI-2 | 89.6% | — |
| SimpleBench | — | 26.3% |
| Kagi LLM Benchmark | — | 64.4% |
| NYT Connections (extended) | 90.1% | — |
| ARC-AGI-1 | 95.5% | — |
| CritPt | 30.9% | — |
| EBR-Bench | 53.3% | — |
| Mystery Game Puzzles | 56% | — |
| DTBench | 97.3% | — |
| LMCA | 59.1% | — |
| ForecastBench | — | 60.2 |
Math GPT-6 Sol leads
GPT-6 Sol: 87.2 (#7), Kimi K2 (Jul 2025): 42.7 (#83)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Math | 1402 | 1397 |
| FrontierMath (Tiers 1-3) | 89.8% | — |
| FrontierMath Tier 4 | 90% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
| Omni-MATH | — | 65.4% |
| FrontierMath (Feb 2025 set) | — | 21.4% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge GPT-6 Sol leads
GPT-6 Sol: 64.8 (#15), Kimi K2 (Jul 2025): 37.3 (#157)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| Vectara Hallucination Rate | 6.5% | 17.9% |
| LMArena Expert | 1439 | 1365 |
| GPQA Diamond | 94.3% | — |
| SimpleQA Verified | 60.7% | — |
| MMLU-Pro | — | 81.9% |
| Confabulations | — | 20.4% |
| GPQA (HELM) | — | 65.3% |
Multimodal Not comparable
GPT-6 Sol: 47.6 (#10), Kimi K2 (Jul 2025): —
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Vision | 1245 | — |
| Blueprint-Bench 2 | 36.9% | — |
| Furniture Assembly | 58.3% | — |
Multilingual Too close to call
GPT-6 Sol: 50.5 (#118), Kimi K2 (Jul 2025): 49.6 (#130)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | 1385 | 1372 |
| LMArena Chinese | 1405 | 1415 |
| LMArena French | 1410 | 1379 |
| LMArena German | 1390 | 1387 |
| LMArena Japanese | 1385 | 1349 |
| LMArena Korean | 1341 | 1325 |
| LMArena Russian | 1401 | 1385 |
| LMArena Spanish | 1384 | 1386 |
Instruction Following GPT-6 Sol leads
GPT-6 Sol: 74.5 (#94), Kimi K2 (Jul 2025): 71.1 (#156)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Instruction Following | 1412 | 1348 |
| IFEval | — | 85% |
Long Context GPT-6 Sol leads
GPT-6 Sol: 43.1 (#108), Kimi K2 (Jul 2025): 41.2 (#145)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Longer Query | 1411 | 1353 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 17.6% |
Writing & Preference GPT-6 Sol leads
GPT-6 Sol: 71.9 (#18), Kimi K2 (Jul 2025): 62.3 (#78)
| Benchmark | GPT-6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | 1395 | 1380 |
| LMArena Creative Writing | 1378 | 1350 |
| EQ-Bench Creative Writing | 2125 | 1666 |
| LMArena Multi-Turn | 1412 | 1371 |
| Short-Story Creative Writing | — | 85.6% |
| WildBench | — | 86.2% |
Frequently asked questions
Is GPT-6 Sol better than Kimi K2 (Jul 2025)?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 41.2 on the Noometry Index. Kimi K2 (Jul 2025) costs 4.0× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-6 Sol or Kimi K2 (Jul 2025)?
Kimi K2 (Jul 2025) is cheaper. It lists at $0.57 per million input tokens and $2.30 per million output tokens; GPT-6 Sol lists at $2 and $10.
Is GPT-6 Sol or Kimi K2 (Jul 2025) better for coding?
GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 42.4 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 262K.
How many benchmarks do GPT-6 Sol and Kimi K2 (Jul 2025) share?
21 benchmarks have published results for both models. GPT-6 Sol has 45 scored results on Noometry and Kimi K2 (Jul 2025) has 42.