Model comparison
gpt-oss-120b vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 36.3 on the Noometry Index. gpt-oss-120b costs 498× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 10 shared benchmarks.
Summary
- They share 10 benchmarks with published results for both. gpt-oss-120b scores higher in 1 category and o3-pro in 4 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 31.4.
- The biggest single-benchmark swing is Fiction.LiveBench: 44.4% for gpt-oss-120b and 97.2% for o3-pro.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $20 / $80 for o3-pro.
- o3-pro accepts more context: 200K tokens versus 131K.
- gpt-oss-120b has downloadable open weights; the other is API-only.
Side by side
| gpt-oss-120b | o3-pro | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 36.3 | 42.9 |
| Released | 2025-08-05 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | 131K | 200K |
| Max output | 41K | 100K |
| Input $ / M tokens | $0.037 | $20 |
| Output $ / M tokens | $0.17 | $80 |
| Results tracked | 48 | 12 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding o3-pro leads
gpt-oss-120b: 33.5 (#256), o3-pro: 55.5 (#24)
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| Aider Polyglot | 41.8% | 84.9% |
| WeirdML | 48.2% | 58.2% |
| SWE-bench Verified (bash only) | 26% | — |
| SciCode | 36% | — |
| LMArena Coding | 1380 | — |
| ALE-Bench | 575.62 | — |
| AlgoTune | 1.41 | — |
Agentic & Tool Use Not comparable
gpt-oss-120b: 12.2 (#153), o3-pro: —
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |
| Vending-Bench 2 | -21.53 | — |
Reasoning o3-pro leads
gpt-oss-120b: 20.0 (#245), o3-pro: 23.8 (#171)
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| Kagi LLM Benchmark | 58.6% | 72.1% |
| DTBench | 76.3% | 86.9% |
| LMCA | 22.1% | 38.5% |
| Epoch Capabilities Index | 139.93 | 147.42 |
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | 22.1% | — |
| ARC-AGI-1 | — | 59.3% |
| CritPt | 1.1% | — |
| Chess Puzzles | 20% | — |
| LMArena Hard Prompts | 1364 | — |
| Mystery Game Puzzles | 2% | — |
| Surface Evolver Bench | 25% | — |
Math Not comparable
gpt-oss-120b: 52.5 (#50), o3-pro: —
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | — |
| Omni-MATH | 68.8% | — |
| LMArena Math | 1389 | — |
Knowledge gpt-oss-120b leads
gpt-oss-120b: 42.4 (#96), o3-pro: 29.5 (#238)
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| Confabulations | 15.7% | 14.2% |
| Vectara Hallucination Rate | 14.2% | 23.3% |
| GPQA Diamond | 75.8% | — |
| MMLU-Pro | 79.5% | — |
| GPQA (HELM) | 68.4% | — |
| LMArena Expert | 1356 | — |
Multilingual Not comparable
gpt-oss-120b: 48.0 (#147), o3-pro: —
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| 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 Not comparable
gpt-oss-120b: 69.3 (#173), o3-pro: —
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| IFEval | 83.6% | — |
| LMArena Instruction Following | 1318 | — |
Long Context o3-pro leads
gpt-oss-120b: 31.4 (#278), o3-pro: 72.2 (#1)
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| Fiction.LiveBench | 44.4% | 97.2% |
| LMArena Longer Query | 1319 | — |
Writing & Preference o3-pro leads
gpt-oss-120b: 46.5 (#217), o3-pro: 57.1 (#133)
| Benchmark | gpt-oss-120b | o3-pro |
|---|---|---|
| Short-Story Creative Writing | 77.1% | 84.4% |
| LMArena Text | 1365 | — |
| LMArena Creative Writing | 1275 | — |
| EQ-Bench Creative Writing | 961 | — |
| WildBench | 84.5% | — |
| LMArena Multi-Turn | 1340 | — |
Frequently asked questions
Is gpt-oss-120b better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 36.3 on the Noometry Index. gpt-oss-120b costs 498× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Which is cheaper, gpt-oss-120b or o3-pro?
gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; o3-pro lists at $20 and $80.
Is gpt-oss-120b or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 33.5 in the Noometry coding category.
Which has the bigger context window?
o3-pro does, with 200K tokens against 131K.
How many benchmarks do gpt-oss-120b and o3-pro share?
10 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and o3-pro has 12.