Model comparison
gpt-oss-120b vs Wizardlm 70b
gpt-oss-120b is the stronger model overall, scoring 36.0 to 32.4 on the Noometry Index.
Last verified . 12 shared benchmarks.
MicrosoftSummary
- They share 12 benchmarks with published results for both. gpt-oss-120b scores higher in 5 categories and Wizardlm 70b in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 50.6 to 29.7.
Side by side
| gpt-oss-120b | Wizardlm 70b | |
|---|---|---|
| Provider | OpenAI | Microsoft |
| Noometry Index | 36.0 | 32.4 |
| Released | 2025-08-05 | — |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 41K | — |
| Input $ / M tokens | $0.037 | — |
| Output $ / M tokens | $0.17 | — |
| Results tracked | 48 | 12 |
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Category by category
Coding gpt-oss-120b leads
gpt-oss-120b: 33.2 (#251), Wizardlm 70b: 30.9 (#280)
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| LMArena Coding | 1380 | 1081 |
| SWE-bench Verified (bash only) | 26% | — |
| Aider Polyglot | 41.8% | — |
| SciCode | 36% | — |
| WeirdML | 48.2% | — |
| ALE-Bench | 575.62 | — |
| AlgoTune | 1.41 | — |
Agentic & Tool Use Not comparable
gpt-oss-120b: 12.1 (#145), Wizardlm 70b: —
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |
| Vending-Bench 2 | -21.53 | — |
Reasoning Too close to call
gpt-oss-120b: 19.5 (#236), Wizardlm 70b: 19.8 (#231)
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| LMArena Hard Prompts | 1364 | 1079 |
| SimpleBench | 22.1% | — |
| Kagi LLM Benchmark | 58.6% | — |
| CritPt | 1.1% | — |
| Chess Puzzles | 20% | — |
| Mystery Game Puzzles | 2% | — |
| DTBench | 76.3% | — |
| LMCA | 22.1% | — |
| Surface Evolver Bench | 25% | — |
| Epoch Capabilities Index | 139.94 | — |
Math gpt-oss-120b leads
gpt-oss-120b: 50.6 (#43), Wizardlm 70b: 29.7 (#216)
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| LMArena Math | 1388 | 1116 |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| Omni-MATH | 68.8% | — |
Knowledge Not comparable
gpt-oss-120b: 42.3 (#89), Wizardlm 70b: —
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| GPQA Diamond | 75.8% | — |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| Vectara Hallucination Rate | 14.2% | — |
| GPQA (HELM) | 68.4% | — |
| LMArena Expert | 1356 | — |
Multilingual gpt-oss-120b leads
gpt-oss-120b: 48.2 (#142), Wizardlm 70b: 29.8 (#260)
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| LMArena Non-English | 1350 | 1078 |
| LMArena Chinese | 1384 | 1052 |
| LMArena German | 1355 | 1083 |
| LMArena Russian | 1343 | 1155 |
| LMArena French | 1370 | — |
| LMArena Japanese | 1332 | — |
| LMArena Korean | 1283 | — |
| LMArena Spanish | 1388 | — |
Instruction Following gpt-oss-120b leads
gpt-oss-120b: 69.5 (#168), Wizardlm 70b: 56.5 (#268)
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| LMArena Instruction Following | 1318 | 1093 |
| IFEval | 83.6% | — |
Long Context Wizardlm 70b leads
gpt-oss-120b: 31.4 (#273), Wizardlm 70b: 33.3 (#258)
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| LMArena Longer Query | 1319 | 1097 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference gpt-oss-120b leads
gpt-oss-120b: 46.7 (#213), Wizardlm 70b: 34.9 (#264)
| Benchmark | gpt-oss-120b | Wizardlm 70b |
|---|---|---|
| LMArena Text | 1366 | 1120 |
| LMArena Creative Writing | 1274 | 1149 |
| LMArena Multi-Turn | 1340 | 1108 |
| Short-Story Creative Writing | 77.1% | — |
| EQ-Bench Creative Writing | 961 | — |
| WildBench | 84.5% | — |
Frequently asked questions
Is gpt-oss-120b better than Wizardlm 70b?
gpt-oss-120b is the stronger model overall, scoring 36.0 to 32.4 on the Noometry Index.
Is gpt-oss-120b or Wizardlm 70b better for coding?
gpt-oss-120b scores higher on coding benchmarks: 33.2 versus 30.9 in the Noometry coding category.
How many benchmarks do gpt-oss-120b and Wizardlm 70b share?
12 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Wizardlm 70b has 12.