gpt-oss-120b benchmarks
gpt-oss-120b has 5 published scores in this dataset, from a OpenAI release dated 2025-08-05. Its composite index is 57.3, which places it 22nd of 22 ranked models and 15th among 15 open-weight models. Its strongest area is coding (index 76.5) and its weakest is agentic (index 27.1). Its best placing is on AIME, where its 95.8 ranks 2nd of 5 models with a published score.
Category profile
Index 0–100: each score relative to the best published score on that test.
Model facts
- Lab
- OpenAI
- Type
- Open weights
- Released
- 2025-08-05
- Parameters
- 117B total, 5.1B active (MoE)
- Context
- 128K
- License
- Apache 2.0
gpt-oss-120b hardware requirements and cost
Even at 4-bit it needs about 81 GB (1× H200 (141 GB)), well beyond a home workstation, so most people run it on rented multi-GPU servers. Full BF16 precision needs about 269 GB (4× H100 (320 GB)).
| Precision | Weights | With headroom | Smallest setup |
|---|---|---|---|
| BF16 (full precision) | 234 GB | 269 GB | 4× H100 (320 GB) |
| FP8 / 8-bit | 117 GB | 135 GB | 1× H200 (141 GB) |
| 4-bit (GGUF Q4_K_M) | 70 GB | 81 GB | 1× H200 (141 GB) |
Estimate: parameters × bytes per parameter, plus 15% for the KV cache and runtime at modest context lengths. Long contexts and large batches need more.
Lighter or stronger open models
Open models ranked just above and below on the composite index, with their 4-bit memory needs.
- Step 5 Preview78.7414 GB
- Nemotron 3 Ultra74.4379 GB
- Gemma 4 26B A4B72.917 GBcompare
gpt-oss-120b speed and pricing
Measured figures link to their source; estimates are labelled.
- API output speed
- 212 tok/sArtificial Analysis median · Artificial Analysis
- Time to first token
- 0.53 sOpenRouter model page provider stats
- API price per 1M tokens
- $0.030 in · $0.150 outcheapest provider on OpenRouter: Near AI · OpenRouter endpoints API
Score by test
Rank is among every model with a published score on that test.
Nearby in the composite ranking
Models with the closest composite index.
Head-to-head comparisons
Side-by-side pages built from the tests both models report.
Sources
| Model | Test | Score | Setting | Source |
|---|---|---|---|---|
| gpt-oss-120b | GPQA Diamond | 80.1 | high effort, no tools | gpt-oss model card paper (arXiv 2508.10925), Table 3 |
| gpt-oss-120b | Humanity's Last Exam | 14.9 | high effort, no tools | gpt-oss model card paper (arXiv 2508.10925), Table 3 |
| gpt-oss-120b | Humanity's Last Exam (with tools) | 19.0 | high effort, with tools | gpt-oss model card paper (arXiv 2508.10925), Table 3 |
| gpt-oss-120b | AIME | 95.8 | AIME 2024, high effort, no tools | gpt-oss model card paper (arXiv 2508.10925), Table 3 |
| gpt-oss-120b | SWE-bench Verified | 62.4 | high effort | gpt-oss model card paper (arXiv 2508.10925), Table 3 |
Scores are published results from model cards, lab reports, and public leaderboards, each linked to its source. Settings such as thinking mode or test version differ between sources and are shown next to each score. OpenLLM Buddy catalog models are uncensored fine-tunes; their scores are those of the official base model. Data collected 2026-10-30. How the index works