# gpt-oss-120b vs Qwen3.6 Flash

> Qwen3.6 Flash is the stronger model overall, scoring 38.8 to 36.3 on the Noometry Index. gpt-oss-120b costs 6.0× less per token, which makes it the better buy when Qwen3.6 Flash's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-oss-120b-vs-qwen3-6-flash
- Last updated: 2026-10-12
- Shared benchmarks: 9

## Summary

- They share 9 benchmarks with published results for both. gpt-oss-120b scores higher in 2 categories and Qwen3.6 Flash in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in math, where gpt-oss-120b leads 52.5 to 39.0.
- The biggest single-benchmark swing is Mystery Game Puzzles: 2% for gpt-oss-120b and 18% for Qwen3.6 Flash.
- gpt-oss-120b is cheaper at $0.037 / $0.17 per million input/output tokens, against $0.19 / $1.13 for Qwen3.6 Flash.
- Qwen3.6 Flash accepts more context: 1M tokens versus 131K.
- gpt-oss-120b has downloadable open weights; the other is API-only.

## Snapshot

| | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 36.3 | 38.8 |
| Rank | 217 | 182 |
| Context | 131K | 1M |
| Input $/M | $0.037 | $0.19 |
| Output $/M | $0.17 | $1.13 |
| Weights | Open | Proprietary |

## Coding

- gpt-oss-120b: 33.5 (#256)
- Qwen3.6 Flash: —

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| ALE-Bench | 575.62 | 326.4 |
| SWE-bench Verified (bash only) | 26% | — |
| Aider Polyglot | 41.8% | — |
| SciCode | 36% | — |
| WeirdML | 48.2% | — |
| LMArena Coding | 1380 | — |
| AlgoTune | 1.41 | — |

## Agentic & Tool Use

- gpt-oss-120b: 12.2 (#153)
- Qwen3.6 Flash: —

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| Terminal-Bench | 18.7% | — |
| APEX-Agents | 4.4% | — |
| METR Time Horizons | 56.6% | — |
| Vending-Bench 2 | -21.53 | — |

## Reasoning

- gpt-oss-120b: 20.0 (#245)
- Qwen3.6 Flash: 29.0 (#96)

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| SimpleBench | 22.1% | 35.2% |
| Chess Puzzles | 20% | 20% |
| Mystery Game Puzzles | 2% | 18% |
| DTBench | 76.3% | 77.1% |
| LMCA | 22.1% | 31% |
| Epoch Capabilities Index | 139.93 | 143.26 |
| Kagi LLM Benchmark | 58.6% | — |
| CritPt | 1.1% | — |
| LMArena Hard Prompts | 1364 | — |
| Surface Evolver Bench | 25% | — |

## Math

- gpt-oss-120b: 52.5 (#50)
- Qwen3.6 Flash: 39.0 (#117)

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 88.9% | 84.4% |
| FrontierMath (Tiers 1-3) | — | 22.5% |
| Omni-MATH | 68.8% | — |
| LMArena Math | 1389 | — |
| FrontierMath (Feb 2025 set) | — | 10.3% |
| FrontierMath Tier 4 (v1) | — | 0% |

## Knowledge

- gpt-oss-120b: 42.4 (#96)
- Qwen3.6 Flash: 42.1 (#100)

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| GPQA Diamond | 75.8% | 83.3% |
| SimpleQA Verified | — | 15.9% |
| MMLU-Pro | 79.5% | — |
| Confabulations | 15.7% | — |
| Vectara Hallucination Rate | 14.2% | — |
| GPQA (HELM) | 68.4% | — |
| LMArena Expert | 1356 | — |

## Multilingual

- gpt-oss-120b: 48.0 (#147)
- Qwen3.6 Flash: —

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| LMArena Non-English | 1351 | — |
| LMArena Chinese | 1385 | — |
| LMArena French | 1369 | — |
| LMArena German | 1353 | — |
| LMArena Japanese | 1331 | — |
| LMArena Korean | 1282 | — |
| LMArena Russian | 1343 | — |
| LMArena Spanish | 1389 | — |

## Instruction Following

- gpt-oss-120b: 69.3 (#173)
- Qwen3.6 Flash: —

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| IFEval | 83.6% | — |
| LMArena Instruction Following | 1318 | — |

## Long Context

- gpt-oss-120b: 31.4 (#278)
- Qwen3.6 Flash: —

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| Fiction.LiveBench | 44.4% | — |
| LMArena Longer Query | 1319 | — |

## Writing & Preference

- gpt-oss-120b: 46.5 (#217)
- Qwen3.6 Flash: —

| Benchmark | gpt-oss-120b | Qwen3.6 Flash |
|---|---|---|
| LMArena Text | 1365 | — |
| LMArena Creative Writing | 1275 | — |
| Short-Story Creative Writing | 77.1% | — |
| EQ-Bench Creative Writing | 961 | — |
| WildBench | 84.5% | — |
| LMArena Multi-Turn | 1340 | — |

## FAQ

### Is gpt-oss-120b better than Qwen3.6 Flash?

Qwen3.6 Flash is the stronger model overall, scoring 38.8 to 36.3 on the Noometry Index. gpt-oss-120b costs 6.0× less per token, which makes it the better buy when Qwen3.6 Flash's lead doesn't matter for your workload.

### Which is cheaper, gpt-oss-120b or Qwen3.6 Flash?

gpt-oss-120b is cheaper. It lists at $0.037 per million input tokens and $0.17 per million output tokens; Qwen3.6 Flash lists at $0.19 and $1.13.

### Which has the bigger context window?

Qwen3.6 Flash does, with 1M tokens against 131K.

### How many benchmarks do gpt-oss-120b and Qwen3.6 Flash share?

9 benchmarks have published results for both models. gpt-oss-120b has 48 scored results on Noometry and Qwen3.6 Flash has 13.