# Devstral Small 2505 vs Qwen3.5 397B-A17B

> Qwen3.5 397B-A17B is the stronger model overall, scoring 45.7 to 33.9 on the Noometry Index. Devstral Small 2505 costs 9.0× less per token, which makes it the better buy when Qwen3.5 397B-A17B's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/devstral-small-vs-qwen3-5-397b-a17b
- Last updated: 2026-10-10
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. Devstral Small 2505 scores higher in 0 categories and Qwen3.5 397B-A17B in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5 397B-A17B leads 33.6 to 19.1.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 37.7% for Devstral Small 2505 and 73.7% for Qwen3.5 397B-A17B.
- Devstral Small 2505 is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.60 / $3.60 for Qwen3.5 397B-A17B.
- Qwen3.5 397B-A17B accepts more context: 262K tokens versus 128K.

## Snapshot

| | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 33.9 | 45.7 |
| Rank | 228 | 60 |
| Context | 128K | 262K |
| Input $/M | $0.10 | $0.60 |
| Output $/M | $0.30 | $3.60 |
| Weights | Open | Open |

## Coding

- Devstral Small 2505: 38.6 (#160)
- Qwen3.5 397B-A17B: 41.7 (#108)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| SWE-bench Verified (bash only) | 56.4% | — |
| LMArena WebDev | — | 1400 |
| SciCode | 28.8% | — |
| LMArena Coding | — | 1464 |

## Agentic & Tool Use

- Devstral Small 2505: —
- Qwen3.5 397B-A17B: 33.2 (#51)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| APEX-Agents | — | 24.9% |
| τ²-bench Airline | — | 81.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 84.4% |
| τ²-bench Telecom | — | 97.8% |

## Reasoning

- Devstral Small 2505: 19.1 (#243)
- Qwen3.5 397B-A17B: 33.6 (#62)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| Kagi LLM Benchmark | 37.7% | 73.7% |
| NYT Connections (extended) | — | 58.9% |
| CritPt | 0% | — |
| Chess Puzzles | — | 13% |
| Thematic Generalization | — | 65.1% |
| LMArena Hard Prompts | — | 1448 |
| Mystery Game Puzzles | — | 18% |
| DTBench | — | 87.5% |
| LMCA | — | 37.9% |
| Epoch Capabilities Index | — | 146.64 |

## Math

- Devstral Small 2505: —
- Qwen3.5 397B-A17B: 44.9 (#64)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 31.2% |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| LMArena Math | — | 1455 |

## Knowledge

- Devstral Small 2505: —
- Qwen3.5 397B-A17B: 53.3 (#53)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| GPQA Diamond | — | 86.4% |
| LMArena Expert | — | 1461 |

## Multimodal

- Devstral Small 2505: —
- Qwen3.5 397B-A17B: 40.0 (#42)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Vision | — | 1262 |

## Multilingual

- Devstral Small 2505: —
- Qwen3.5 397B-A17B: 54.0 (#56)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Non-English | — | 1431 |
| LMArena Chinese | — | 1501 |
| LMArena French | — | 1461 |
| LMArena German | — | 1447 |
| LMArena Japanese | — | 1427 |
| LMArena Korean | — | 1382 |
| LMArena Russian | — | 1429 |
| LMArena Spanish | — | 1443 |

## Instruction Following

- Devstral Small 2505: —
- Qwen3.5 397B-A17B: 75.2 (#73)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Instruction Following | — | 1424 |

## Long Context

- Devstral Small 2505: —
- Qwen3.5 397B-A17B: 44.1 (#71)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Longer Query | — | 1442 |

## Writing & Preference

- Devstral Small 2505: —
- Qwen3.5 397B-A17B: 62.5 (#74)

| Benchmark | Devstral Small 2505 | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Text | — | 1438 |
| LMArena Creative Writing | — | 1401 |
| EQ-Bench Creative Writing | — | 1478 |
| LMArena Multi-Turn | — | 1447 |

## FAQ

### Is Devstral Small 2505 better than Qwen3.5 397B-A17B?

Qwen3.5 397B-A17B is the stronger model overall, scoring 45.7 to 33.9 on the Noometry Index. Devstral Small 2505 costs 9.0× less per token, which makes it the better buy when Qwen3.5 397B-A17B's lead doesn't matter for your workload.

### Which is cheaper, Devstral Small 2505 or Qwen3.5 397B-A17B?

Devstral Small 2505 is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Qwen3.5 397B-A17B lists at $0.60 and $3.60.

### Is Devstral Small 2505 or Qwen3.5 397B-A17B better for coding?

Qwen3.5 397B-A17B scores higher on coding benchmarks: 41.7 versus 38.6 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.5 397B-A17B does, with 262K tokens against 128K.

### How many benchmarks do Devstral Small 2505 and Qwen3.5 397B-A17B share?

1 benchmark has published results for both models. Devstral Small 2505 has 4 scored results on Noometry and Qwen3.5 397B-A17B has 36.