Model comparison
Gemini 2.0 Pro vs gpt-oss-120b
Gemini 2.0 Pro is the stronger model overall, scoring 39.1 to 36.3 on the Noometry Index.
Last verified . 5 shared benchmarks.
GoogleSummary
- They share 5 benchmarks with published results for both. Gemini 2.0 Pro scores higher in 4 categories and gpt-oss-120b in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 52.5 to 39.7.
- The biggest single-benchmark swing is GPQA Diamond: 65.7% for Gemini 2.0 Pro and 75.8% for gpt-oss-120b.
- gpt-oss-120b has downloadable open weights; the other is API-only.
Side by side
| Gemini 2.0 Pro | gpt-oss-120b | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 39.1 | 36.3 |
| Released | 2025-02-05 | 2025-08-05 |
| Weights | Proprietary | Open |
| Context window | — | 131K |
| Max output | — | 41K |
| Input $ / M tokens | — | $0.037 |
| Output $ / M tokens | — | $0.17 |
| Results tracked | 14 | 48 |
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Category by category
Coding Gemini 2.0 Pro leads
Gemini 2.0 Pro: 37.8 (#187), gpt-oss-120b: 33.5 (#256)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| Aider Polyglot | 35.6% | 41.8% |
| SWE-bench Verified (bash only) | — | 26% |
| SciCode | — | 36% |
| WeirdML | — | 48.2% |
| LiveBench Coding | 63.5% | — |
| LMArena Coding | — | 1380 |
| ALE-Bench | — | 575.62 |
| AlgoTune | — | 1.41 |
Agentic & Tool Use Not comparable
Gemini 2.0 Pro: —, gpt-oss-120b: 12.2 (#153)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| Terminal-Bench | — | 18.7% |
| APEX-Agents | — | 4.4% |
| METR Time Horizons | — | 56.6% |
| Vending-Bench 2 | — | -21.53 |
Reasoning Gemini 2.0 Pro leads
Gemini 2.0 Pro: 22.3 (#198), gpt-oss-120b: 20.0 (#245)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| Epoch Capabilities Index | 135.06 | 139.93 |
| SimpleBench | — | 22.1% |
| Kagi LLM Benchmark | — | 58.6% |
| CritPt | — | 1.1% |
| Chess Puzzles | — | 20% |
| EnigmaEval | 0.7% | — |
| LiveBench Reasoning | 60.1% | — |
| LMArena Hard Prompts | — | 1364 |
| Mystery Game Puzzles | — | 2% |
| DTBench | — | 76.3% |
| LiveBench Data Analysis | 68% | — |
| LMCA | — | 22.1% |
| Surface Evolver Bench | — | 25% |
| LiveBench | 65.1% | — |
Math gpt-oss-120b leads
Gemini 2.0 Pro: 39.7 (#100), gpt-oss-120b: 52.5 (#50)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| Omni-MATH | — | 68.8% |
| LiveBench Math | 71% | — |
| LMArena Math | — | 1389 |
| MATH Level 5 | 83.5% | — |
Knowledge gpt-oss-120b leads
Gemini 2.0 Pro: 36.5 (#167), gpt-oss-120b: 42.4 (#96)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| GPQA Diamond | 65.7% | 75.8% |
| Confabulations | 18.4% | 15.7% |
| MMLU-Pro | — | 79.5% |
| Vectara Hallucination Rate | — | 14.2% |
| GPQA (HELM) | — | 68.4% |
| LMArena Expert | — | 1356 |
Multilingual Not comparable
Gemini 2.0 Pro: —, gpt-oss-120b: 48.0 (#147)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| LMArena Non-English | — | 1351 |
| LMArena Chinese | — | 1385 |
| LMArena French | — | 1369 |
| LMArena German | — | 1353 |
| LMArena Japanese | — | 1331 |
| LMArena Korean | — | 1282 |
| LMArena Russian | — | 1343 |
| LMArena Spanish | — | 1389 |
Instruction Following Gemini 2.0 Pro leads
Gemini 2.0 Pro: 75.5 (#59), gpt-oss-120b: 69.3 (#173)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| LiveBench Instruction Following | 83.4% | — |
| IFEval | — | 83.6% |
| LMArena Instruction Following | — | 1318 |
Long Context gpt-oss-120b leads
Gemini 2.0 Pro: 29.2 (#292), gpt-oss-120b: 31.4 (#278)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| Fiction.LiveBench | 41.7% | 44.4% |
| LMArena Longer Query | — | 1319 |
Writing & Preference Gemini 2.0 Pro leads
Gemini 2.0 Pro: 52.7 (#165), gpt-oss-120b: 46.5 (#217)
| Benchmark | Gemini 2.0 Pro | gpt-oss-120b |
|---|---|---|
| LMArena Text | — | 1365 |
| LMArena Creative Writing | — | 1275 |
| Short-Story Creative Writing | — | 77.1% |
| EQ-Bench Creative Writing | — | 961 |
| WildBench | — | 84.5% |
| LMArena Multi-Turn | — | 1340 |
| LiveBench Language | 44.9% | — |
Frequently asked questions
Is Gemini 2.0 Pro better than gpt-oss-120b?
Gemini 2.0 Pro is the stronger model overall, scoring 39.1 to 36.3 on the Noometry Index.
Is Gemini 2.0 Pro or gpt-oss-120b better for coding?
Gemini 2.0 Pro scores higher on coding benchmarks: 37.8 versus 33.5 in the Noometry coding category.
How many benchmarks do Gemini 2.0 Pro and gpt-oss-120b share?
5 benchmarks have published results for both models. Gemini 2.0 Pro has 14 scored results on Noometry and gpt-oss-120b has 48.