Model comparison
gpt-oss-120b vs Kimi K2 (Jul 2025)
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 36.3 on the Noometry Index. gpt-oss-120b costs 14× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Last verified . 36 shared benchmarks.
Summary
- They share 36 benchmarks with published results for both. gpt-oss-120b scores higher in 2 categories and Kimi K2 (Jul 2025) in 7 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Kimi K2 (Jul 2025) leads 32.4 to 12.2.
- The biggest single-benchmark swing is SWE-bench Verified (bash only): 26% for gpt-oss-120b and 63.4% for Kimi K2 (Jul 2025).
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 131K.
Side by side
| gpt-oss-120b | Kimi K2 (Jul 2025) | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 36.3 | 41.2 |
| Released | 2025-08-05 | 2025-07-12 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 41K | 262K |
| Input $ / M tokens | $0.037 | $0.57 |
| Output $ / M tokens | $0.17 | $2.30 |
| Results tracked | 48 | 42 |
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Category by category
Coding Kimi K2 (Jul 2025) leads
gpt-oss-120b: 33.5 (#256), Kimi K2 (Jul 2025): 42.4 (#102)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| SWE-bench Verified (bash only) | 26% | 63.4% |
| Aider Polyglot | 41.8% | 59.1% |
| WeirdML | 48.2% | 42.8% |
| LMArena Coding | 1380 | 1399 |
| ALE-Bench | 575.62 | 597.5 |
| SciCode | 36% | — |
| GSO | — | 4.9% |
| AlgoTune | 1.41 | — |
Agentic & Tool Use Kimi K2 (Jul 2025) leads
gpt-oss-120b: 12.2 (#153), Kimi K2 (Jul 2025): 32.4 (#64)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| Terminal-Bench | 18.7% | 35.7% |
| METR Time Horizons | 56.6% | 59.2% |
| APEX-Agents | 4.4% | — |
| Berkeley Function Calling Leaderboard | — | 59.1% |
| Vending-Bench 2 | -21.53 | — |
Reasoning Kimi K2 (Jul 2025) leads
gpt-oss-120b: 20.0 (#245), Kimi K2 (Jul 2025): 23.3 (#179)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| SimpleBench | 22.1% | 26.3% |
| Kagi LLM Benchmark | 58.6% | 64.4% |
| LMArena Hard Prompts | 1364 | 1384 |
| Epoch Capabilities Index | 139.93 | 146.01 |
| CritPt | 1.1% | — |
| Chess Puzzles | 20% | — |
| Mystery Game Puzzles | 2% | — |
| DTBench | 76.3% | — |
| LMCA | 22.1% | — |
| Surface Evolver Bench | 25% | — |
| ForecastBench | — | 60.2 |
Math gpt-oss-120b leads
gpt-oss-120b: 52.5 (#50), Kimi K2 (Jul 2025): 42.7 (#83)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| Omni-MATH | 68.8% | 65.4% |
| LMArena Math | 1389 | 1397 |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| FrontierMath (Feb 2025 set) | — | 21.4% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge gpt-oss-120b leads
gpt-oss-120b: 42.4 (#96), Kimi K2 (Jul 2025): 37.3 (#157)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| MMLU-Pro | 79.5% | 81.9% |
| Confabulations | 15.7% | 20.4% |
| Vectara Hallucination Rate | 14.2% | 17.9% |
| GPQA (HELM) | 68.4% | 65.3% |
| LMArena Expert | 1356 | 1365 |
| GPQA Diamond | 75.8% | — |
Multilingual Kimi K2 (Jul 2025) leads
gpt-oss-120b: 48.0 (#147), Kimi K2 (Jul 2025): 49.6 (#130)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | 1351 | 1372 |
| LMArena Chinese | 1385 | 1415 |
| LMArena French | 1369 | 1379 |
| LMArena German | 1353 | 1387 |
| LMArena Japanese | 1331 | 1349 |
| LMArena Korean | 1282 | 1325 |
| LMArena Russian | 1343 | 1385 |
| LMArena Spanish | 1389 | 1386 |
Instruction Following Kimi K2 (Jul 2025) leads
gpt-oss-120b: 69.3 (#173), Kimi K2 (Jul 2025): 71.1 (#156)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| IFEval | 83.6% | 85% |
| LMArena Instruction Following | 1318 | 1348 |
Long Context Kimi K2 (Jul 2025) leads
gpt-oss-120b: 31.4 (#278), Kimi K2 (Jul 2025): 41.2 (#145)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| Fiction.LiveBench | 44.4% | 66.7% |
| LMArena Longer Query | 1319 | 1353 |
| CL-bench | — | 17.6% |
Writing & Preference Kimi K2 (Jul 2025) leads
gpt-oss-120b: 46.5 (#217), Kimi K2 (Jul 2025): 62.3 (#78)
| Benchmark | gpt-oss-120b | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | 1365 | 1380 |
| LMArena Creative Writing | 1275 | 1350 |
| Short-Story Creative Writing | 77.1% | 85.6% |
| EQ-Bench Creative Writing | 961 | 1666 |
| WildBench | 84.5% | 86.2% |
| LMArena Multi-Turn | 1340 | 1371 |
Frequently asked questions
Is gpt-oss-120b better than Kimi K2 (Jul 2025)?
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 36.3 on the Noometry Index. gpt-oss-120b costs 14× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Which is cheaper, gpt-oss-120b or Kimi K2 (Jul 2025)?
gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is gpt-oss-120b or Kimi K2 (Jul 2025) better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 33.5 in the Noometry coding category.
Which has the bigger context window?
Kimi K2 (Jul 2025) does, with 262K tokens against 131K.
How many benchmarks do gpt-oss-120b and Kimi K2 (Jul 2025) share?
36 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Kimi K2 (Jul 2025) has 42.