# gpt-oss-20b vs Qwen2.5 72B Instruct

> gpt-oss-20b and Qwen2.5 72B Instruct score almost the same on the Noometry Index (32.5 vs 31.9), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/gpt-oss-20b-vs-qwen2-5-72b-instruct
- Last updated: 2026-10-12
- Shared benchmarks: 27

## Summary

- They share 27 benchmarks with published results for both. gpt-oss-20b scores higher in 4 categories and Qwen2.5 72B Instruct in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-20b leads 39.4 to 19.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 65.3% for gpt-oss-20b and 8.1% for Qwen2.5 72B Instruct.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $1.40 / $5.60 for Qwen2.5 72B Instruct.

## Snapshot

| | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 32.5 | 31.9 |
| Rank | 255 | 267 |
| Context | 131K | 131K |
| Input $/M | $0.018 | $1.40 |
| Output $/M | $0.09 | $5.60 |
| Weights | Open | Open |

## Coding

- gpt-oss-20b: 37.6 (#192)
- Qwen2.5 72B Instruct: 33.2 (#260)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| WeirdML | 40.9% | 16% |
| LMArena Coding | 1306 | 1292 |
| SciCode | 34.4% | — |
| BigCodeBench Instruct | — | 45.8% |
| BigCodeBench Complete | — | 55.9% |
| ALE-Bench | 566.05 | — |

## Agentic & Tool Use

- gpt-oss-20b: 9.3 (#154)
- Qwen2.5 72B Instruct: 22.1 (#133)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| Terminal-Bench | 3.4% | — |
| TheAgentCompany | — | 5.7% |
| BALROG | — | 16.2% |
| METR Time Horizons | — | 35.8% |

## Reasoning

- gpt-oss-20b: 19.3 (#261)
- Qwen2.5 72B Instruct: 22.3 (#199)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1274 | 1271 |
| DTBench | 68% | 62.9% |
| LMCA | 14.5% | 13.4% |
| Epoch Capabilities Index | 137.82 | 129 |
| Kagi LLM Benchmark | 53.2% | — |
| CritPt | 1.4% | — |
| Chess Puzzles | 4% | — |
| BIG-Bench Hard | — | 79.8% |
| ForecastBench | — | 57.5 |
| HellaSwag | — | 84.8% |
| PIQA | — | 82.6% |
| WinoGrande | — | 82.3% |

## Math

- gpt-oss-20b: 39.4 (#103)
- Qwen2.5 72B Instruct: 19.3 (#287)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 65.3% | 8.1% |
| Omni-MATH | 56.5% | 33% |
| LMArena Math | 1317 | 1283 |
| MATH Level 5 | — | 63.2% |

## Knowledge

- gpt-oss-20b: 34.6 (#195)
- Qwen2.5 72B Instruct: 27.0 (#253)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| GPQA Diamond | 60.8% | 49.1% |
| MMLU-Pro | 74% | 63.1% |
| GPQA (HELM) | 59.4% | 42.6% |
| LMArena Expert | 1258 | 1245 |
| Confabulations | — | 19.1% |
| ARC (AI2) Challenge | — | 94.5% |
| MMLU | — | 85.3% |
| TriviaQA | — | 71.9% |

## Multilingual

- gpt-oss-20b: 42.2 (#197)
- Qwen2.5 72B Instruct: 41.0 (#213)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Non-English | 1268 | 1252 |
| LMArena Chinese | 1314 | 1272 |
| LMArena German | 1255 | 1234 |
| LMArena Japanese | 1244 | 1180 |
| LMArena Korean | 1236 | 1188 |
| LMArena Russian | 1278 | 1264 |
| LMArena Spanish | 1267 | 1256 |
| LMArena French | — | 1280 |

## Instruction Following

- gpt-oss-20b: 61.8 (#240)
- Qwen2.5 72B Instruct: 65.5 (#221)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| IFEval | 73.2% | 80.6% |
| LMArena Instruction Following | 1236 | 1254 |

## Long Context

- gpt-oss-20b: 37.9 (#209)
- Qwen2.5 72B Instruct: 38.9 (#188)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1250 | 1282 |

## Writing & Preference

- gpt-oss-20b: 35.5 (#265)
- Qwen2.5 72B Instruct: 46.7 (#215)

| Benchmark | gpt-oss-20b | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Text | 1287 | 1269 |
| LMArena Creative Writing | 1201 | 1221 |
| WildBench | 73.7% | 80.2% |
| LMArena Multi-Turn | 1268 | 1272 |
| EQ-Bench Creative Writing | 666 | — |

## FAQ

### Is gpt-oss-20b better than Qwen2.5 72B Instruct?

gpt-oss-20b and Qwen2.5 72B Instruct score almost the same on the Noometry Index (32.5 vs 31.9), so choose on price, context window or the category you care about most.

### Which is cheaper, gpt-oss-20b or Qwen2.5 72B Instruct?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Qwen2.5 72B Instruct lists at $1.40 and $5.60.

### Is gpt-oss-20b or Qwen2.5 72B Instruct better for coding?

gpt-oss-20b scores higher on coding benchmarks: 37.6 versus 33.2 in the Noometry coding category.

### Which has the bigger context window?

Both accept 131K tokens.

### How many benchmarks do gpt-oss-20b and Qwen2.5 72B Instruct share?

27 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Qwen2.5 72B Instruct has 43.