# GPT-5.1-Codex vs Qwen2.5 72B Instruct

> GPT-5.1-Codex is the stronger model overall, scoring 38.2 to 31.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-1-codex-vs-qwen2-5-72b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. GPT-5.1-Codex scores higher in 3 categories and Qwen2.5 72B Instruct in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.1-Codex leads 37.8 to 22.0.
- Qwen2.5 72B Instruct is cheaper at $1.40 / $5.60 per million input/output tokens, against $1.25 / $10 for GPT-5.1-Codex.
- GPT-5.1-Codex accepts more context: 400K tokens versus 131K.
- Qwen2.5 72B Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 38.2 | 31.5 |
| Rank | 178 | 259 |
| Context | 400K | 131K |
| Input $/M | $1.25 | $1.40 |
| Output $/M | $10 | $5.60 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.1-Codex: 41.7 (#107)
- Qwen2.5 72B Instruct: 32.8 (#256)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| SWE-bench Verified (bash only) | 66% | — |
| LMArena WebDev | 1337 | — |
| WeirdML | — | 16% |
| BigCodeBench Instruct | — | 45.8% |
| LMArena Coding | — | 1293 |
| BigCodeBench Complete | — | 55.9% |
| ALE-Bench | 1,245 | — |

## Agentic & Tool Use

- GPT-5.1-Codex: 37.8 (#32)
- Qwen2.5 72B Instruct: 22.0 (#124)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| METR Time Horizons | 70.8% | 35.8% |
| Terminal-Bench | 60.4% | — |
| TheAgentCompany | — | 5.7% |
| BALROG | — | 16.2% |

## Reasoning

- GPT-5.1-Codex: —
- Qwen2.5 72B Instruct: 21.4 (#197)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Hard Prompts | — | 1271 |
| DTBench | — | 62.9% |
| LMCA | — | 13.4% |
| BIG-Bench Hard | — | 79.8% |
| Epoch Capabilities Index | — | 129.01 |
| ForecastBench | — | 57.5 |
| HellaSwag | — | 84.8% |
| PIQA | — | 82.6% |
| WinoGrande | — | 82.3% |

## Math

- GPT-5.1-Codex: 29.3 (#218)
- Qwen2.5 72B Instruct: 18.1 (#281)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 8.1% |
| ProofBench | 9% | — |
| Omni-MATH | — | 33% |
| LMArena Math | — | 1283 |
| MATH Level 5 | — | 63.2% |

## Knowledge

- GPT-5.1-Codex: —
- Qwen2.5 72B Instruct: 26.9 (#247)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| GPQA Diamond | — | 49.1% |
| MMLU-Pro | — | 63.1% |
| Confabulations | — | 19.1% |
| GPQA (HELM) | — | 42.6% |
| LMArena Expert | — | 1245 |
| ARC (AI2) Challenge | — | 94.5% |
| MMLU | — | 85.3% |
| TriviaQA | — | 71.9% |

## Multilingual

- GPT-5.1-Codex: —
- Qwen2.5 72B Instruct: 41.2 (#208)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Non-English | — | 1252 |
| LMArena Chinese | — | 1272 |
| LMArena French | — | 1279 |
| LMArena German | — | 1234 |
| LMArena Japanese | — | 1180 |
| LMArena Korean | — | 1188 |
| LMArena Russian | — | 1264 |
| LMArena Spanish | — | 1255 |

## Instruction Following

- GPT-5.1-Codex: —
- Qwen2.5 72B Instruct: 65.7 (#216)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| IFEval | — | 80.6% |
| LMArena Instruction Following | — | 1254 |

## Long Context

- GPT-5.1-Codex: —
- Qwen2.5 72B Instruct: 38.9 (#183)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Longer Query | — | 1282 |

## Writing & Preference

- GPT-5.1-Codex: —
- Qwen2.5 72B Instruct: 46.9 (#210)

| Benchmark | GPT-5.1-Codex | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Text | — | 1269 |
| LMArena Creative Writing | — | 1221 |
| WildBench | — | 80.2% |
| LMArena Multi-Turn | — | 1272 |

## FAQ

### Is GPT-5.1-Codex better than Qwen2.5 72B Instruct?

GPT-5.1-Codex is the stronger model overall, scoring 38.2 to 31.5 on the Noometry Index.

### Which is cheaper, GPT-5.1-Codex or Qwen2.5 72B Instruct?

Qwen2.5 72B Instruct is cheaper. It lists at $1.40 per million input tokens and $5.60 per million output tokens; GPT-5.1-Codex lists at $1.25 and $10.

### Is GPT-5.1-Codex or Qwen2.5 72B Instruct better for coding?

GPT-5.1-Codex scores higher on coding benchmarks: 41.7 versus 32.8 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.1-Codex does, with 400K tokens against 131K.

### How many benchmarks do GPT-5.1-Codex and Qwen2.5 72B Instruct share?

1 benchmark has published results for both models. GPT-5.1-Codex has 6 scored results on Noometry and Qwen2.5 72B Instruct has 43.