Model comparison
GPT-5.6 Sol vs Kimi K2 (Jul 2025)
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 40.9 on the Noometry Index. Kimi K2 (Jul 2025) costs 8.0× less per token, which makes it the better buy when GPT-5.6 Sol's lead doesn't matter for your workload.
Last verified . 24 shared benchmarks.
Summary
- They share 24 benchmarks with published results for both. GPT-5.6 Sol scores higher in 9 categories and Kimi K2 (Jul 2025) in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.6 Sol leads 74.7 to 22.7.
- The biggest single-benchmark swing is WeirdML: 89.4% for GPT-5.6 Sol and 42.8% for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) is cheaper at $0.57 / $2.30 per million input/output tokens, against $4 / $20 for GPT-5.6 Sol.
- GPT-5.6 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-5.6 Sol | Kimi K2 (Jul 2025) | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 64.4 | 40.9 |
| Released | 2026-07-09 | 2025-07-12 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $4 | $0.57 |
| Output $ / M tokens | $20 | $2.30 |
| Results tracked | 64 | 42 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.6 Sol leads
GPT-5.6 Sol: 61.1 (#7), Kimi K2 (Jul 2025): 43.1 (#83)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| WeirdML | 89.4% | 42.8% |
| LMArena Coding | 1493 | 1399 |
| ALE-Bench | 2,177 | 597.5 |
| DeepSWE | 72.7% | — |
| FrontierCode | 47.5% | — |
| SWE-bench Verified (bash only) | — | 63.4% |
| Aider Polyglot | — | 59.1% |
| CursorBench | 41.7% | — |
| LMArena WebDev | 1619 | — |
| FrontierSWE | 32.2% | — |
| SciCode | 57.1% | — |
| GSO | — | 4.9% |
| MirrorCode | 20% | — |
Agentic & Tool Use GPT-5.6 Sol leads
GPT-5.6 Sol: 50.2 (#7), Kimi K2 (Jul 2025): 32.2 (#59)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| Terminal-Bench | — | 35.7% |
| APEX-Agents | 51.4% | — |
| Berkeley Function Calling Leaderboard | — | 59.1% |
| OSWorld 2.0 | 27.3% | — |
| τ²-bench Banking | 46.9% | — |
| PostTrainBench | 36.2% | — |
| BALROG | 60% | — |
| GBAEval | 52.6% | — |
| GDP.pdf | 30.7% | — |
| LMArena Search | 1257 | — |
| METR Time Horizons | — | 59.2% |
| Vending-Bench 2 | 9,619 | — |
Reasoning GPT-5.6 Sol leads
GPT-5.6 Sol: 74.7 (#6), Kimi K2 (Jul 2025): 22.7 (#173)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| SimpleBench | 71.7% | 26.3% |
| Kagi LLM Benchmark | 67% | 64.4% |
| LMArena Hard Prompts | 1481 | 1384 |
| Epoch Capabilities Index | 161.99 | 146.02 |
| ARC-AGI-2 | 92.5% | — |
| NYT Connections (extended) | 93.8% | — |
| ARC-AGI-1 | 97.5% | — |
| CritPt | 32.3% | — |
| Chess Puzzles | 64% | — |
| EnigmaEval | 37.1% | — |
| EBR-Bench | 44.8% | — |
| Mystery Game Puzzles | 58% | — |
| DTBench | 96% | — |
| LMCA | 59.2% | — |
| Surface Evolver Bench | 93.1% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | — | 60.2 |
Math GPT-5.6 Sol leads
GPT-5.6 Sol: 85.5 (#7), Kimi K2 (Jul 2025): 40.1 (#81)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Math | 1472 | 1396 |
| FrontierMath (Tiers 1-3) | 89.1% | — |
| FrontierMath Tier 4 | 82.9% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
| Omni-MATH | — | 65.4% |
| FrontierMath (Feb 2025 set) | — | 21.4% |
| FrontierMath Erdős | 0% | — |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge GPT-5.6 Sol leads
GPT-5.6 Sol: 64.3 (#16), Kimi K2 (Jul 2025): 36.9 (#153)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| Vectara Hallucination Rate | 12.4% | 17.9% |
| LMArena Expert | 1517 | 1363 |
| GPQA Diamond | 93.5% | — |
| SimpleQA Verified | 69.7% | — |
| MMLU-Pro | — | 81.9% |
| Confabulations | — | 20.4% |
| GPQA (HELM) | — | 65.3% |
Multimodal Not comparable
GPT-5.6 Sol: 48.9 (#8), Kimi K2 (Jul 2025): —
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Vision | 1281 | — |
| Blueprint-Bench 2 | 33.6% | — |
| Furniture Assembly | 56.7% | — |
| LMArena Document | 1483 | — |
Multilingual GPT-5.6 Sol leads
GPT-5.6 Sol: 55.4 (#32), Kimi K2 (Jul 2025): 49.8 (#125)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | 1450 | 1372 |
| LMArena Chinese | 1523 | 1416 |
| LMArena French | 1475 | 1379 |
| LMArena German | 1476 | 1386 |
| LMArena Japanese | 1475 | 1349 |
| LMArena Korean | 1434 | 1324 |
| LMArena Russian | 1466 | 1384 |
| LMArena Spanish | 1449 | 1383 |
Instruction Following GPT-5.6 Sol leads
GPT-5.6 Sol: 77.8 (#16), Kimi K2 (Jul 2025): 71.3 (#151)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Instruction Following | 1480 | 1347 |
| IFEval | — | 85% |
Long Context GPT-5.6 Sol leads
GPT-5.6 Sol: 45.3 (#42), Kimi K2 (Jul 2025): 41.2 (#140)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Longer Query | 1479 | 1353 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 17.6% |
Writing & Preference GPT-5.6 Sol leads
GPT-5.6 Sol: 73.5 (#12), Kimi K2 (Jul 2025): 62.5 (#76)
| Benchmark | GPT-5.6 Sol | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | 1456 | 1380 |
| LMArena Creative Writing | 1450 | 1349 |
| EQ-Bench Creative Writing | 1972 | 1666 |
| LMArena Multi-Turn | 1456 | 1371 |
| Short-Story Creative Writing | — | 85.6% |
| WildBench | — | 86.2% |
| EQ-Bench 4 | 1250 | — |
Frequently asked questions
Is GPT-5.6 Sol better than Kimi K2 (Jul 2025)?
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 40.9 on the Noometry Index. Kimi K2 (Jul 2025) costs 8.0× less per token, which makes it the better buy when GPT-5.6 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-5.6 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-5.6 Sol lists at $4 and $20.
Is GPT-5.6 Sol or Kimi K2 (Jul 2025) better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 61.1 versus 43.1 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Sol does, with 1.05M tokens against 262K.
How many benchmarks do GPT-5.6 Sol and Kimi K2 (Jul 2025) share?
24 benchmarks have published results for both models. GPT-5.6 Sol has 64 scored results on Noometry and Kimi K2 (Jul 2025) has 42.