Model profile
GPT-OSS 120B
Evidence coverage
27 of 321 tracked benchmarks are published. 2 are verified and 25 provisional. 8 of 8 categories are measured.
- Published / tracked
- 27 / 321
- Verified
- 2
- Provisional
- 25
- Categories with evidence
- 8 / 8
Evidence by category
- Agentic9 benchmarksMixed evidence
- Coding4 benchmarksMixed evidence
- Reasoning2 benchmarksReported
- Knowledge8 benchmarksReported
- Math1 benchmarkReported
- Multilingual1 benchmarkReported
- Multimodal1 benchmarkReported
- Inst. Following1 benchmarkReported
GPT-OSS 120B ranks #116 out of 200 models on the public leaderboard with an overall score of 50.08/100. It also ranks #63 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
GPT-OSS 120B is a open weight model with a 128K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
GPT-OSS 120B sits inside the GPT-OSS family alongside GPT-OSS 20B. This profile currently has 27 of 321 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Knowledge (#32), while its weakest is Coding (#80). This performance profile makes it particularly effective for knowledge-intensive tasks like research, analysis, and factual Q&A.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 49.89–50.28
- DeepSeek Coder 2.0DeepSeekCompare#11450.28DeepSeek Coder 2.0 is #114 with a score of 50.28.
- Seed 1.6ByteDanceCompare#11550.23Seed 1.6 is #115 with a score of 50.23.
- GPT-OSS 120BCurrent modelOpenAI#11650.08GPT-OSS 120B is #116 with a score of 50.08.
- Nemotron 3 Super 100BNVIDIACompare#11750.08Nemotron 3 Super 100B is #117 with a score of 50.08.
- o4-mini (high)OpenAICompare#11849.98o4-mini (high) is #118 with a score of 49.98.
- DeepSeekMath V2DeepSeekCompare#11949.89DeepSeekMath V2 is #119 with a score of 49.89.
- Qwen2.5-1MAlibabaCompare#12049.89Qwen2.5-1M is #120 with a score of 49.89.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
- Knowledge39%Eligible cohort rank #32 of 52Category score 66.6
- Agentic36%Eligible cohort rank #76 of 119Category score 44.9
- Coding35%Eligible cohort rank #80 of 122Category score 47.5
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #76 of 119Percentile 36thWeight 22%9 benchmarksMixed sources | 44.9 | #76 of 119 | 36th | 22% | 9 benchmarks | Mixed sources |
| CodingRank #80 of 122Percentile 35thWeight 20%4 benchmarksMixed sources | 47.5 | #80 of 122 | 35th | 20% | 4 benchmarks | Mixed sources |
| ReasoningRank Not rankedWeight 17%2 benchmarksReported | 58.4 | Not ranked | Not available | 17% | 2 benchmarks | Reported |
| KnowledgeRank #32 of 52Percentile 39thWeight 12%8 benchmarksReported | 66.6 | #32 of 52 | 39th | 12% | 8 benchmarks | Reported |
| MathWeight 5%1 benchmarkReported | Score pending | Not ranked | Not available | 5% | 1 benchmark | Reported |
| MultilingualRank Not rankedWeight 7%1 benchmarkReported | 70.0 | Not ranked | Not available | 7% | 1 benchmark | Reported |
| MultimodalRank Not rankedWeight 12%1 benchmarkReported | 48.0 | Not ranked | Not available | 12% | 1 benchmark | Reported |
| Inst. FollowingRank Not rankedWeight 5%1 benchmarkReported | 79.0 | Not ranked | Not available | 5% | 1 benchmark | Reported |
Chatbot Arena performance
Scroll horizontally to inspect confidence intervals and vote counts.
| View | Elo | Confidence interval | Votes |
|---|---|---|---|
| Text Overall | 1353 | ±4.3 | 30,629 |
| Coding | 1390 | ±7.7 | 6,491 |
| Math | 1382 | ±13.6 | 1,795 |
| Instruction Following | 1325 | ±7.0 | 7,817 |
| Creative Writing | 1278 | ±9.8 | 3,950 |
| Multi-turn | 1328 | ±8.7 | 5,003 |
| Hard Prompts | 1362 | ±5.7 | 14,765 |
| Hard Prompts (English) | 1367 | ±7.2 | 7,634 |
| Longer Query | 1324 | ±7.8 | 6,458 |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic9 benchmarks
Artificial Analysis Agentic Index
τ²-Bench Tool-Agent-User Evaluation
GDPval-AA normalized
Gert Labs Composite Game Benchmark
Artificial Analysis EnterpriseOps-Gym
Artificial Analysis Harvey LAB-AA
Artificial Analysis ITBench-AA
Coding4 benchmarks
Artificial Analysis Coding Index
Artificial Analysis SciCode
Artificial Analysis LiveCodeBench
Reasoning2 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge8 benchmarks
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Artificial Analysis Openness Index
Artificial Analysis MMLU-Pro
Math1 benchmark
Artificial Analysis AIME 2025
Multilingual1 benchmark
Artificial Analysis Global-MMLU-Lite
Multimodal1 benchmark
Design Arena Website Elo
Inst. Following1 benchmark
Artificial Analysis IFBench
Frequently Asked Questions
How does GPT-OSS 120B perform overall in AI benchmarks?
GPT-OSS 120B has 27 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is GPT-OSS 120B good for knowledge and understanding?
GPT-OSS 120B ranks #32 out of 52 models in knowledge and understanding benchmarks with an average score of 66.6. There are stronger options in this category.
Is GPT-OSS 120B good for coding and programming?
GPT-OSS 120B ranks #80 out of 122 models in coding and programming benchmarks with an average score of 47.5. There are stronger options in this category.
Is GPT-OSS 120B good for mathematics?
GPT-OSS 120B has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is GPT-OSS 120B good for reasoning and logic?
GPT-OSS 120B has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is GPT-OSS 120B good for agentic tool use and computer tasks?
GPT-OSS 120B ranks #76 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 44.9. There are stronger options in this category.
Is GPT-OSS 120B good for multimodal and grounded tasks?
GPT-OSS 120B has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.
Is GPT-OSS 120B good for instruction following?
GPT-OSS 120B has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
Is GPT-OSS 120B good for multilingual tasks?
GPT-OSS 120B has visible benchmark coverage in multilingual tasks, but BenchLM does not currently assign it a global category rank there.
Is GPT-OSS 120B open source?
Yes, GPT-OSS 120B is an open weight model created by OpenAI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Which sibling models are related to GPT-OSS 120B?
GPT-OSS 120B belongs to the GPT-OSS family. Related variants on BenchLM include GPT-OSS 20B.
Does GPT-OSS 120B have full benchmark coverage on BenchLM?
Not yet. GPT-OSS 120B currently has 27 published benchmark scores out of the 321 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of GPT-OSS 120B?
GPT-OSS 120B has a published context window of 128K, which determines how much text it can process in a single interaction.
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