Model comparison
GPT-4o mini vs gpt-oss-120b
gpt-oss-120b is the stronger model overall, scoring 36.3 to 25.5 on the Noometry Index.
Last verified . 36 shared benchmarks.
Summary
- They share 36 benchmarks with published results for both. GPT-4o mini scores higher in 2 categories and gpt-oss-120b in 7 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 52.5 to 10.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 6.9% for GPT-4o mini and 88.9% for gpt-oss-120b.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $0.15 / $0.60 for GPT-4o mini.
- gpt-oss-120b accepts more context: 131K tokens versus 128K.
- gpt-oss-120b has downloadable open weights; the other is API-only.
Side by side
| GPT-4o mini | gpt-oss-120b | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 25.5 | 36.3 |
| Released | 2024-07-18 | 2025-08-05 |
| Weights | Proprietary | Open |
| Context window | 128K | 131K |
| Max output | 16K | 41K |
| Input $ / M tokens | $0.15 | $0.037 |
| Output $ / M tokens | $0.60 | $0.17 |
| Results tracked | 60 | 48 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding gpt-oss-120b leads
GPT-4o mini: 22.0 (#335), gpt-oss-120b: 33.5 (#256)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| Aider Polyglot | 3.6% | 41.8% |
| WeirdML | 11.8% | 48.2% |
| LMArena Coding | 1290 | 1380 |
| SWE-bench Verified (bash only) | — | 26% |
| SciCode | — | 36% |
| BigCodeBench Instruct | 46.1% | — |
| LiveBench Coding | 43.1% | — |
| BigCodeBench Complete | 57.4% | — |
| ALE-Bench | — | 575.62 |
| AlgoTune | — | 1.41 |
| HumanEval+ | 83.5% | — |
| MBPP+ | 72.2% | — |
Agentic & Tool Use GPT-4o mini leads
GPT-4o mini: 27.5 (#101), gpt-oss-120b: 12.2 (#153)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| Terminal-Bench | — | 18.7% |
| APEX-Agents | — | 4.4% |
| BALROG | 17.4% | — |
| METR Time Horizons | — | 56.6% |
| Vending-Bench 2 | — | -21.53 |
Reasoning gpt-oss-120b leads
GPT-4o mini: 8.7 (#347), gpt-oss-120b: 20.0 (#245)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| SimpleBench | 10.7% | 22.1% |
| Kagi LLM Benchmark | 28.8% | 58.6% |
| Chess Puzzles | 0% | 20% |
| LMArena Hard Prompts | 1267 | 1364 |
| Mystery Game Puzzles | 12% | 2% |
| DTBench | 54.4% | 76.3% |
| LMCA | 10.4% | 22.1% |
| Epoch Capabilities Index | 126.56 | 139.93 |
| ARC-AGI-2 | 0% | — |
| CritPt | — | 1.1% |
| LiveBench Reasoning | 32.8% | — |
| LiveBench Data Analysis | 50% | — |
| Surface Evolver Bench | — | 25% |
| LiveBench | 41.3% | — |
| PIQA | 88.7% | — |
Math gpt-oss-120b leads
GPT-4o mini: 10.4 (#314), gpt-oss-120b: 52.5 (#50)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 6.9% | 88.9% |
| Omni-MATH | 28% | 68.8% |
| LMArena Math | 1267 | 1389 |
| FrontierMath (Tiers 1-3) | 0.7% | — |
| LiveBench Math | 36.3% | — |
| MATH Level 5 | 52.6% | — |
| GSM8K | 91.3% | — |
Knowledge gpt-oss-120b leads
GPT-4o mini: 17.7 (#284), gpt-oss-120b: 42.4 (#96)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| GPQA Diamond | 37.7% | 75.8% |
| MMLU-Pro | 60.3% | 79.5% |
| Confabulations | 37.2% | 15.7% |
| GPQA (HELM) | 36.8% | 68.4% |
| LMArena Expert | 1235 | 1356 |
| SimpleQA Verified | 8.3% | — |
| Vectara Hallucination Rate | — | 14.2% |
| BoolQ | 88.7% | — |
| MMLU | 81.8% | — |
Multimodal Not comparable
GPT-4o mini: 25.9 (#122), gpt-oss-120b: —
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| LMArena Vision | 1066 | — |
| Video-MME | 64.8% | — |
| GeoBench | 64% | — |
| VPCT | 34% | — |
Multilingual gpt-oss-120b leads
GPT-4o mini: 42.0 (#199), gpt-oss-120b: 48.0 (#147)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| LMArena Non-English | 1266 | 1351 |
| LMArena Chinese | 1265 | 1385 |
| LMArena French | 1297 | 1369 |
| LMArena German | 1272 | 1353 |
| LMArena Japanese | 1216 | 1331 |
| LMArena Korean | 1195 | 1282 |
| LMArena Russian | 1275 | 1343 |
| LMArena Spanish | 1276 | 1389 |
Instruction Following gpt-oss-120b leads
GPT-4o mini: 61.9 (#239), gpt-oss-120b: 69.3 (#173)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| IFEval | 78.2% | 83.6% |
| LMArena Instruction Following | 1258 | 1318 |
| LiveBench Instruction Following | 56.8% | — |
Long Context GPT-4o mini leads
GPT-4o mini: 39.1 (#186), gpt-oss-120b: 31.4 (#278)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| LMArena Longer Query | 1289 | 1319 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference gpt-oss-120b leads
GPT-4o mini: 39.5 (#248), gpt-oss-120b: 46.5 (#217)
| Benchmark | GPT-4o mini | gpt-oss-120b |
|---|---|---|
| LMArena Text | 1286 | 1365 |
| LMArena Creative Writing | 1268 | 1275 |
| Short-Story Creative Writing | 67.2% | 77.1% |
| EQ-Bench Creative Writing | 873 | 961 |
| WildBench | 79.1% | 84.5% |
| LMArena Multi-Turn | 1285 | 1340 |
| LiveBench Language | 28.6% | — |
Frequently asked questions
Is GPT-4o mini better than gpt-oss-120b?
gpt-oss-120b is the stronger model overall, scoring 36.3 to 25.5 on the Noometry Index.
Which is cheaper, GPT-4o mini or gpt-oss-120b?
gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; GPT-4o mini lists at $0.15 and $0.60.
Is GPT-4o mini or gpt-oss-120b better for coding?
gpt-oss-120b scores higher on coding benchmarks: 33.5 versus 22.0 in the Noometry coding category.
Which has the bigger context window?
gpt-oss-120b does, with 131K tokens against 128K.
How many benchmarks do GPT-4o mini and gpt-oss-120b share?
36 benchmarks have published results for both models. GPT-4o mini has 60 scored results on Noometry and gpt-oss-120b has 48.