# DeepSeek-V3.1 vs Qwen3.7 Flash

> DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 39.5 on the Noometry Index. Qwen3.7 Flash costs 7.7× less per token, which makes it the better buy when DeepSeek-V3.1's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-qwen3-7-flash
- Last updated: 2026-10-10
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. DeepSeek-V3.1 scores higher in 0 categories and Qwen3.7 Flash in 3 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.7 Flash leads 48.9 to 43.0.
- Qwen3.7 Flash is cheaper at $0.03 / $0.13 per million input/output tokens, against $0.25 / $0.95 for DeepSeek-V3.1.
- Qwen3.7 Flash accepts more context: 1M tokens versus 164K.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 42.2 | 39.5 |
| Rank | 106 | 152 |
| Context | 164K | 1M |
| Input $/M | $0.25 | $0.03 |
| Output $/M | $0.95 | $0.13 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.1: 39.8 (#140)
- Qwen3.7 Flash: —

| Benchmark | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| WeirdML | 38.4% | — |
| LMArena Coding | 1417 | — |

## Reasoning

- DeepSeek-V3.1: 27.3 (#109)
- Qwen3.7 Flash: 27.3 (#108)

| Benchmark | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| Epoch Capabilities Index | 139.92 | 144.62 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| NYT Connections (extended) | — | 43.8% |
| Chess Puzzles | — | 23% |
| LMArena Hard Prompts | 1417 | — |
| Mystery Game Puzzles | — | 15% |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| ForecastBench | 58 | — |

## Math

- DeepSeek-V3.1: 36.1 (#125)
- Qwen3.7 Flash: 37.3 (#100)

| Benchmark | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 19.3% |
| OTIS Mock AIME 2024-2025 | — | 86.7% |
| LMArena Math | 1420 | — |

## Knowledge

- DeepSeek-V3.1: 43.0 (#86)
- Qwen3.7 Flash: 48.9 (#69)

| Benchmark | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| GPQA Diamond | — | 82.3% |
| Vectara Hallucination Rate | 5.5% | — |
| LMArena Expert | 1403 | — |

## Multilingual

- DeepSeek-V3.1: 51.8 (#100)
- Qwen3.7 Flash: —

| Benchmark | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| LMArena Non-English | 1400 | — |
| LMArena Chinese | 1470 | — |
| LMArena French | 1447 | — |
| LMArena German | 1412 | — |
| LMArena Japanese | 1374 | — |
| LMArena Korean | 1337 | — |
| LMArena Russian | 1405 | — |
| LMArena Spanish | 1429 | — |

## Instruction Following

- DeepSeek-V3.1: 74.1 (#105)
- Qwen3.7 Flash: —

| Benchmark | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| LMArena Instruction Following | 1400 | — |

## Long Context

- DeepSeek-V3.1: 36.3 (#227)
- Qwen3.7 Flash: —

| Benchmark | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| Fiction.LiveBench | 52.8% | — |
| LMArena Longer Query | 1422 | — |

## Writing & Preference

- DeepSeek-V3.1: 60.5 (#93)
- Qwen3.7 Flash: —

| Benchmark | DeepSeek-V3.1 | Qwen3.7 Flash |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1401 | — |
| EQ-Bench Creative Writing | 1436 | — |
| LMArena Multi-Turn | 1408 | — |

## FAQ

### Is DeepSeek-V3.1 better than Qwen3.7 Flash?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 39.5 on the Noometry Index. Qwen3.7 Flash costs 7.7× less per token, which makes it the better buy when DeepSeek-V3.1's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-V3.1 or Qwen3.7 Flash?

Qwen3.7 Flash is cheaper. It lists at $0.03 per million input tokens and $0.13 per million output tokens; DeepSeek-V3.1 lists at $0.25 and $0.95.

### Which has the bigger context window?

Qwen3.7 Flash does, with 1M tokens against 164K.

### How many benchmarks do DeepSeek-V3.1 and Qwen3.7 Flash share?

1 benchmark has published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Qwen3.7 Flash has 7.