# DeepSeek LLM 67B vs Qwen2.5 7B Instruct

> Qwen2.5 7B Instruct is the stronger model overall, scoring 29.0 to 24.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-llm-67b-vs-qwen2-5-7b-instruct
- Last updated: 2026-10-12
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 1 category and Qwen2.5 7B Instruct in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen2.5 7B Instruct leads 48.8 to 31.6.
- The biggest single-benchmark swing is GPQA Diamond: 24.6% for DeepSeek LLM 67B and 35.5% for Qwen2.5 7B Instruct.

## Snapshot

| | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 24.9 | 29.0 |
| Rank | 347 | 320 |
| Context | — | 131K |
| Input $/M | — | $0.17 |
| Output $/M | — | $0.70 |
| Weights | Open | Open |

## Coding

- DeepSeek LLM 67B: 31.9 (#278)
- Qwen2.5 7B Instruct: 36.5 (#208)

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1096 | — |
| BigCodeBench Complete | — | 46.1% |

## Agentic & Tool Use

- DeepSeek LLM 67B: —
- Qwen2.5 7B Instruct: 23.8 (#124)

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| BALROG | — | 7.8% |

## Reasoning

- DeepSeek LLM 67B: 16.5 (#304)
- Qwen2.5 7B Instruct: 14.8 (#322)

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| Chess Puzzles | 0% | 0% |
| Epoch Capabilities Index | 110.5 | 118.51 |
| LMArena Hard Prompts | 1070 | — |
| DTBench | — | 47.7% |
| LMCA | — | 6.4% |

## Math

- DeepSeek LLM 67B: 8.7 (#324)
- Qwen2.5 7B Instruct: 12.6 (#306)

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 2.5% |
| Omni-MATH | — | 29.4% |
| LMArena Math | 1108 | — |
| MATH Level 5 | 6.4% | — |

## Knowledge

- DeepSeek LLM 67B: 7.0 (#313)
- Qwen2.5 7B Instruct: 17.0 (#286)

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| GPQA Diamond | 24.6% | 35.5% |
| MMLU-Pro | — | 53.9% |
| GPQA (HELM) | — | 34.1% |
| MMLU | — | 72.9% |

## Multilingual

- DeepSeek LLM 67B: 29.4 (#267)
- Qwen2.5 7B Instruct: —

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Non-English | 1073 | — |
| LMArena Chinese | 1132 | — |

## Instruction Following

- DeepSeek LLM 67B: 55.4 (#277)
- Qwen2.5 7B Instruct: 63.2 (#231)

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| IFEval | — | 74.1% |
| LMArena Instruction Following | 1079 | — |

## Long Context

- DeepSeek LLM 67B: 33.1 (#265)
- Qwen2.5 7B Instruct: —

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Longer Query | 1092 | — |

## Writing & Preference

- DeepSeek LLM 67B: 31.6 (#282)
- Qwen2.5 7B Instruct: 48.8 (#195)

| Benchmark | DeepSeek LLM 67B | Qwen2.5 7B Instruct |
|---|---|---|
| LMArena Text | 1105 | — |
| LMArena Creative Writing | 1067 | — |
| WildBench | — | 73.1% |
| LMArena Multi-Turn | 1082 | — |

## FAQ

### Is DeepSeek LLM 67B better than Qwen2.5 7B Instruct?

Qwen2.5 7B Instruct is the stronger model overall, scoring 29.0 to 24.9 on the Noometry Index.

### Is DeepSeek LLM 67B or Qwen2.5 7B Instruct better for coding?

Qwen2.5 7B Instruct scores higher on coding benchmarks: 36.5 versus 31.9 in the Noometry coding category.

### How many benchmarks do DeepSeek LLM 67B and Qwen2.5 7B Instruct share?

4 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and Qwen2.5 7B Instruct has 15.