# DeepSeek-V2.5 (Sep 2024) vs Qwen2.5 72B Instruct

> DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 31.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v2-5-vs-qwen2-5-72b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 7 categories and Qwen2.5 72B Instruct in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek-V2.5 (Sep 2024) leads 33.3 to 18.1.

## Snapshot

| | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 37.0 | 31.5 |
| Rank | 197 | 259 |
| Context | — | 131K |
| Input $/M | — | $1.40 |
| Output $/M | — | $5.60 |
| Weights | Open | Open |

## Coding

- DeepSeek-V2.5 (Sep 2024): 31.3 (#274)
- Qwen2.5 72B Instruct: 32.8 (#256)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| BigCodeBench Instruct | 48.6% | 45.8% |
| LMArena Coding | 1310 | 1293 |
| BigCodeBench Complete | 53.2% | 55.9% |
| Aider Polyglot | 17.8% | — |
| WeirdML | — | 16% |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |

## Agentic & Tool Use

- DeepSeek-V2.5 (Sep 2024): —
- Qwen2.5 72B Instruct: 22.0 (#124)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| TheAgentCompany | — | 5.7% |
| BALROG | — | 16.2% |
| METR Time Horizons | — | 35.8% |

## Reasoning

- DeepSeek-V2.5 (Sep 2024): 24.5 (#145)
- Qwen2.5 72B Instruct: 21.4 (#197)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1289 | 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

- DeepSeek-V2.5 (Sep 2024): 33.3 (#177)
- Qwen2.5 72B Instruct: 18.1 (#281)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Math | 1289 | 1283 |
| OTIS Mock AIME 2024-2025 | — | 8.1% |
| Omni-MATH | — | 33% |
| MATH Level 5 | — | 63.2% |

## Knowledge

- DeepSeek-V2.5 (Sep 2024): 34.2 (#190)
- Qwen2.5 72B Instruct: 26.9 (#247)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Expert | 1266 | 1245 |
| GPQA Diamond | — | 49.1% |
| MMLU-Pro | — | 63.1% |
| Confabulations | — | 19.1% |
| GPQA (HELM) | — | 42.6% |
| ARC (AI2) Challenge | — | 94.5% |
| MMLU | — | 85.3% |
| TriviaQA | — | 71.9% |

## Multilingual

- DeepSeek-V2.5 (Sep 2024): 42.7 (#188)
- Qwen2.5 72B Instruct: 41.2 (#208)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Non-English | 1273 | 1252 |
| LMArena Chinese | 1317 | 1272 |
| LMArena French | 1288 | 1279 |
| LMArena German | 1258 | 1234 |
| LMArena Japanese | 1228 | 1180 |
| LMArena Korean | 1209 | 1188 |
| LMArena Russian | 1289 | 1264 |
| LMArena Spanish | 1248 | 1255 |

## Instruction Following

- DeepSeek-V2.5 (Sep 2024): 67.7 (#189)
- Qwen2.5 72B Instruct: 65.7 (#216)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1280 | 1254 |
| IFEval | — | 80.6% |

## Long Context

- DeepSeek-V2.5 (Sep 2024): 39.5 (#169)
- Qwen2.5 72B Instruct: 38.9 (#183)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1301 | 1282 |

## Writing & Preference

- DeepSeek-V2.5 (Sep 2024): 50.0 (#182)
- Qwen2.5 72B Instruct: 46.9 (#210)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | Qwen2.5 72B Instruct |
|---|---|---|
| LMArena Text | 1294 | 1269 |
| LMArena Creative Writing | 1285 | 1221 |
| LMArena Multi-Turn | 1297 | 1272 |
| WildBench | — | 80.2% |

## FAQ

### Is DeepSeek-V2.5 (Sep 2024) better than Qwen2.5 72B Instruct?

DeepSeek-V2.5 (Sep 2024) is the stronger model overall, scoring 37.0 to 31.5 on the Noometry Index.

### Is DeepSeek-V2.5 (Sep 2024) or Qwen2.5 72B Instruct better for coding?

Qwen2.5 72B Instruct scores higher on coding benchmarks: 32.8 versus 31.3 in the Noometry coding category.

### How many benchmarks do DeepSeek-V2.5 (Sep 2024) and Qwen2.5 72B Instruct share?

19 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and Qwen2.5 72B Instruct has 43.