OpenAI, open weights
gpt-oss-120b
gpt-oss-120b by OpenAI ranks 217th of 354 ranked models on the Noometry Index as of October 2026, with a score of 36.3. Its strongest category is math, where it ranks 50th. API pricing starts at $0.037 per million input tokens and $0.17 per million output tokens, with a 131K-token context window.
Last verified
Specifications
- Noometry rank
- #217 of 354
- Index score
- 36.3
- Evidence
- Confirmed 48 results
- Provider
- OpenAI
- Released
- August 5, 2025
- Weights
- Open weights
- Reasoning
- Yes
- Context window
- 131K
- Max output
- 41K
- Input price
- $0.037 / M
- Output price
- $0.17 / M
- Blended price
- $0.0703 / M
- Output speed
- 55 tokens/s Kagi
- Value
- #6 of 219
- Knowledge cutoff
- August 2025
- Input
- text
- Hugging Face
- openai/gpt-oss-120b
Category scores
Each category score combines every public result we have in that category.
- Coding 33.5
- Agentic & Tool Use 12.2
- Reasoning 20.0
- Math 52.5
- Knowledge 42.4
- Multilingual 48.0
- Instruction Following 69.3
- Long Context 31.4
- Writing & Preference 46.5
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 33.5 | #256 | 5 |
| Agentic & Tool Use | 12.2 | #153 | 2 |
| Reasoning | 20.0 | #245 | 9 |
| Math | 52.5 | #50 | 3 |
| Knowledge | 42.4 | #96 | 6 |
| Multilingual | 48.0 | #147 | 1 |
| Instruction Following | 69.3 | #173 | 2 |
| Long Context | 31.4 | #278 | 2 |
| Writing & Preference | 46.5 | #217 | 6 |
Strengths and weaknesses
Categories where gpt-oss-120b places highest and lowest among the models ranked in each, with its score against that category's median.
Strongest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Math | 52.5 | +15.9 | #50 of 327, top 16% |
| Knowledge | 42.4 | +5.0 | #96 of 314, top 31% |
| Multilingual | 48.0 | +0.6 | #147 of 297, top 50% |
Weakest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Agentic & Tool Use | 12.2 | −18.2 | #153 of 154, top 100% |
| Long Context | 31.4 | −9.5 | #278 of 296, top 94% |
| Coding | 33.5 | −5.3 | #256 of 340, top 76% |
Closest competitors
The models ranked just above and below gpt-oss-120b. When scores are this close, price and speed are often the better way to choose.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| Llama 3.1 Nemotron Ultra 253b v1 | #213 | 36.7 | — | — | Compare |
| Granite 4.0 H Small | #214 | 36.5 | — | — | Compare |
| Command A | #215 | 36.5 | $4.38 | 28 | Compare |
| Grok Build 0.1 | #216 | 36.4 | $1.25 | — | Compare |
| Mistral Medium | #218 | 36.3 | $3 | 68 | Compare |
| GPT-4.1 | #219 | 35.9 | $3.50 | 116 | Compare |
| Deepseek Coder v2 | #220 | 35.9 | — | — | Compare |
| C4ai Aya Expanse 32b | #221 | 35.9 | — | — | Compare |
Sponsored placements are available on pages like this one. Advertise on Noometry
Benchmark results
Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.
Coding
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| SWE-bench Verified (bash only) | 26% | #33 of 39, top 85% | SWE-bench | 2025-08-07 | |
| Aider Polyglot | 41.8% | #26 of 44, top 60% | high | Epoch AI | |
| Aider Polyglot | 41.8% | #26 of 44, top 60% | high | Epoch AI | |
| SciCode | 34% | high | Epoch AI | ||
| SciCode | 36% | #93 of 121, top 77% | low | Epoch AI | |
| WeirdML | 48.2% | #51 of 119, top 43% | high | Epoch AI | |
| WeirdML | 48.2% | #51 of 119, top 43% | high | Epoch AI | |
| WeirdML | 41.9% | medium | Epoch AI | ||
| LMArena Coding | 1380 | #150 of 294, top 52% | LMArena | 2026-10-08 | |
| ALE-Bench | 575.62 | #82 of 105, top 79% | Epoch AI | ||
| AlgoTune | 1.41 | #14 of 18, top 78% | high | Epoch AI |
Agentic & Tool Use
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Terminal-Bench | 18.7% | #38 of 41, top 93% | Epoch AI | ||
| APEX-Agents | 4.4% | #49 of 49, top 100% | Epoch AI | ||
| METR Time Horizons | 56.6% | #20 of 32, top 63% | Epoch AI | ||
| Vending-Bench 2 | -21.53 | #58 of 60, top 97% | Epoch AI |
Reasoning
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| SimpleBench | 22.1% | #72 of 77, top 94% | Epoch AI | ||
| Kagi LLM Benchmark | 58.6% | #43 of 99, top 44% | Kagi LLM Benchmark | ||
| CritPt | 1.1% | #81 of 134, top 61% | high | Epoch AI | |
| CritPt | 0% | low | Epoch AI | ||
| Chess Puzzles | 20% | #58 of 129, top 45% | high | Epoch AI | 2025-12-11 |
| LMArena Hard Prompts | 1364 | #151 of 297, top 51% | LMArena | 2026-10-08 | |
| Mystery Game Puzzles | 0% | high | Epoch AI | 2026-08-27 | |
| Mystery Game Puzzles | 2% | #74 of 74, top 100% | medium | Epoch AI | 2026-08-27 |
| DTBench | 76.3% | #85 of 151, top 57% | high | Epoch AI | |
| LMCA | 22.1% | #91 of 125, top 73% | high | Epoch AI | |
| Surface Evolver Bench | 25% | #23 of 25, top 92% | Epoch AI | ||
| Epoch Capabilities Index | 139.93 | #108 of 213, top 51% | Epoch AI | 2025-08-05 |
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | #55 of 173, top 32% | high | Epoch AI | 2025-12-11 |
| Omni-MATH | 68.8% | #5 of 57, top 9% | HELM Capabilities | ||
| LMArena Math | 1389 | #138 of 285, top 49% | LMArena | 2026-10-08 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| GPQA Diamond | 75.8% | #92 of 186, top 50% | high | Epoch AI | 2025-12-11 |
| MMLU-Pro | 79.5% | #17 of 58, top 30% | HELM Capabilities | ||
| Confabulations (lower is better) | 15.7% | #21 of 51, top 42% | medium reasoning | Lech Mazur benchmarks | |
| Vectara Hallucination Rate (lower is better) | 14.2% | #83 of 96, top 87% | Vectara Hallucination Leaderboard | ||
| GPQA (HELM) | 68.4% | #12 of 57, top 22% | HELM Capabilities | ||
| LMArena Expert | 1356 | #152 of 273, top 56% | LMArena | 2026-10-08 |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1351 | #147 of 297, top 50% | LMArena | 2026-10-08 | |
| LMArena Chinese | 1385 | #147 of 285, top 52% | LMArena | 2026-10-08 | |
| LMArena French | 1369 | #136 of 223, top 61% | LMArena | 2026-10-08 | |
| LMArena German | 1353 | #128 of 231, top 56% | LMArena | 2026-10-08 | |
| LMArena Japanese | 1331 | #109 of 211, top 52% | LMArena | 2026-10-08 | |
| LMArena Korean | 1282 | #138 of 213, top 65% | LMArena | 2026-10-08 | |
| LMArena Russian | 1343 | #149 of 283, top 53% | LMArena | 2026-10-08 | |
| LMArena Spanish | 1389 | #121 of 226, top 54% | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| IFEval | 83.6% | #27 of 57, top 48% | HELM Capabilities | ||
| LMArena Instruction Following | 1318 | #164 of 298, top 56% | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| Fiction.LiveBench | 36.1% | Epoch AI | |||
| Fiction.LiveBench | 44.4% | #41 of 47, top 88% | high | Epoch AI | |
| LMArena Longer Query | 1319 | #173 of 291, top 60% | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1365 | #147 of 297, top 50% | LMArena | 2026-10-08 | |
| LMArena Creative Writing | 1275 | #187 of 295, top 64% | LMArena | 2026-10-08 | |
| Short-Story Creative Writing | 77.1% | #18 of 39, top 47% | Epoch AI | ||
| EQ-Bench Creative Writing | 961 | #97 of 115, top 85% | EQ-Bench | ||
| WildBench | 84.5% | #14 of 57, top 25% | HELM Capabilities | ||
| LMArena Multi-Turn | 1340 | #162 of 295, top 55% | LMArena | 2026-10-08 |
API pricing by provider
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
|---|---|---|---|---|
| bedrock | $0.15 | $0.60 | — | 2026-10-10 |
| cerebras | $0.35 | $0.75 | — | 2026-10-10 |
| deepinfra | $0.037 | $0.17 | — | 2026-10-10 |
| fireworks | $0.15 | $0.60 | $0.015 | 2026-10-10 |
| groq | $0.15 | $0.60 | $0.075 | 2026-10-10 |
| openrouter | $0.037 | $0.17 | — | 2026-10-10 |
| together | $0.15 | $0.60 | — | 2026-10-10 |
| vertex | $0.09 | $0.36 | — | 2026-10-10 |
Compare gpt-oss-120b
- gpt-oss-120b vs Grok Build 0.1
- gpt-oss-120b vs Mistral Medium
- gpt-oss-120b vs Command A
- gpt-oss-120b vs GPT-4.1
- gpt-oss-120b vs Granite 4.0 H Small
- gpt-oss-120b vs Deepseek Coder v2
- gpt-oss-120b vs Claude Fable 5.1
- gpt-oss-120b vs Gemini 3.8 Flash
- gpt-oss-120b vs Kimi K3
- gpt-oss-120b vs Grok 4.6
- gpt-oss-120b vs Qwen3.8 Max
- gpt-oss-120b vs GLM-5.3
- gpt-oss-120b vs Muse Spark 1.3
- gpt-oss-120b vs DeepSeek V4 Pro
Other OpenAI models
- GPT-6 Astra70.8
- GPT-6.1 Sol65.6
- GPT-5.6 Sol65.0
- GPT-5.5 Pro64.3
- GPT-5.563.4
- GPT-6 Sol61.8
- GPT-5.459.4
- GPT-5.6 Terra59.2
Frequently asked questions
How good is gpt-oss-120b?
gpt-oss-120b by OpenAI ranks 217th of 354 ranked models on the Noometry Index as of October 2026, with a score of 36.3. Its strongest category is math, where it ranks 50th. API pricing starts at $0.037 per million input tokens and $0.17 per million output tokens, with a 131K-token context window.
How much does gpt-oss-120b cost?
gpt-oss-120b costs $0.037 per million input tokens and $0.17 per million output tokens on deepinfra.
What is gpt-oss-120b's context window?
gpt-oss-120b accepts up to 131K tokens of input and can write up to 41K tokens in one response.
Is gpt-oss-120b open source?
Yes. gpt-oss-120b's weights are downloadable from Hugging Face (openai/gpt-oss-120b); check the license for commercial terms.
How fast is gpt-oss-120b?
gpt-oss-120b generated about 55 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.
What are gpt-oss-120b's strengths and weaknesses?
Relative to other ranked models, gpt-oss-120b places best in math, knowledge, multilingual and lowest in agentic & tool use, long context, coding.
What is gpt-oss-120b best at?
Its best category is math, where it ranks 50th on Noometry.