# DeepSeek-R1 vs Qwen1.5-7B

> DeepSeek-R1 is the stronger model overall, scoring 42.0 to 30.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-r1-vs-qwen1-5-7b
- Last updated: 2026-10-10
- Shared benchmarks: 12

## Summary

- They share 12 benchmarks with published results for both. DeepSeek-R1 scores higher in 7 categories and Qwen1.5-7B in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-R1 leads 61.5 to 29.8.
- Qwen1.5-7B has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 42.0 | 30.8 |
| Rank | 110 | 270 |
| Context | 164K | — |
| Input $/M | $0.50 | — |
| Output $/M | $2.15 | — |
| Weights | Proprietary | Open |

## Coding

- DeepSeek-R1: 45.9 (#63)
- Qwen1.5-7B: 31.6 (#271)

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| LMArena Coding | 1427 | 1107 |
| Aider Polyglot | 71.4% | — |
| SciCode | 35.7% | — |
| WeirdML | 41.6% | — |
| LiveBench Coding | 66.7% | — |
| ALE-Bench | 804.12 | — |
| AlgoTune | 1.7 | — |

## Agentic & Tool Use

- DeepSeek-R1: 30.4 (#68)
- Qwen1.5-7B: —

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| DeepResearch Bench | 35.1% | — |
| BALROG | 34.9% | — |
| METR Time Horizons | 53.8% | — |

## Reasoning

- DeepSeek-R1: 18.7 (#253)
- Qwen1.5-7B: 19.5 (#237)

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| LMArena Hard Prompts | 1415 | 1066 |
| ARC-AGI-2 | 1.3% | — |
| SimpleBench | 40.8% | — |
| Kagi LLM Benchmark | 69.4% | — |
| ARC-AGI-1 | 21.2% | — |
| CritPt | 1.1% | — |
| LiveBench Reasoning | 83.2% | — |
| LiveBench Data Analysis | 69.8% | — |
| Epoch Capabilities Index | 141.3 | — |
| ForecastBench | 60 | — |
| LiveBench | 71.6% | — |

## Math

- DeepSeek-R1: 42.0 (#70)
- Qwen1.5-7B: 29.0 (#222)

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| LMArena Math | 1401 | 1080 |
| OTIS Mock AIME 2024-2025 | 66.4% | — |
| Omni-MATH | 42.4% | — |
| LiveBench Math | 80.7% | — |
| MATH Level 5 | 96.6% | — |

## Knowledge

- DeepSeek-R1: 44.3 (#81)
- Qwen1.5-7B: 28.2 (#239)

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| LMArena Expert | 1394 | 1055 |
| GPQA Diamond | 76.3% | — |
| MMLU-Pro | 79.3% | — |
| Confabulations | 12.7% | — |
| Vectara Hallucination Rate | 11.3% | — |
| GPQA (HELM) | 66.6% | — |
| MMLU | — | 62.6% |

## Multilingual

- DeepSeek-R1: 52.6 (#80)
- Qwen1.5-7B: 28.6 (#266)

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| LMArena Non-English | 1412 | 1058 |
| LMArena Chinese | 1443 | 1140 |
| LMArena Russian | 1423 | 1006 |
| LMArena French | 1415 | — |
| LMArena German | 1405 | — |
| LMArena Japanese | 1394 | — |
| LMArena Korean | 1359 | — |
| LMArena Spanish | 1410 | — |

## Instruction Following

- DeepSeek-R1: 72.2 (#138)
- Qwen1.5-7B: 54.4 (#276)

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| LMArena Instruction Following | 1382 | 1058 |
| LiveBench Instruction Following | 80.5% | — |
| IFEval | 78.4% | — |

## Long Context

- DeepSeek-R1: 45.4 (#36)
- Qwen1.5-7B: 33.1 (#261)

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| LMArena Longer Query | 1391 | 1090 |
| Fiction.LiveBench | 75% | — |

## Writing & Preference

- DeepSeek-R1: 61.5 (#84)
- Qwen1.5-7B: 29.8 (#288)

| Benchmark | DeepSeek-R1 | Qwen1.5-7B |
|---|---|---|
| LMArena Text | 1428 | 1084 |
| LMArena Creative Writing | 1406 | 1035 |
| LMArena Multi-Turn | 1404 | 1061 |
| Short-Story Creative Writing | 83% | — |
| EQ-Bench Creative Writing | 1500 | — |
| WildBench | 82.8% | — |
| LiveBench Language | 48.5% | — |

## FAQ

### Is DeepSeek-R1 better than Qwen1.5-7B?

DeepSeek-R1 is the stronger model overall, scoring 42.0 to 30.8 on the Noometry Index.

### Is DeepSeek-R1 or Qwen1.5-7B better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 45.9 versus 31.6 in the Noometry coding category.

### How many benchmarks do DeepSeek-R1 and Qwen1.5-7B share?

12 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Qwen1.5-7B has 13.