# Mistral Small vs Qwen3-Coder 480B-A35B Instruct

> Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 38.1 to 33.4 on the Noometry Index. Mistral Small costs 11× less per token, which makes it the better buy when Qwen3-Coder 480B-A35B Instruct's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/mistral-small-vs-qwen3-coder-480b-a35b-instruct
- Last updated: 2026-10-10
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. Mistral Small scores higher in 1 category and Qwen3-Coder 480B-A35B Instruct in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-Coder 480B-A35B Instruct leads 37.6 to 16.4.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 37.8% for Mistral Small and 49.5% for Qwen3-Coder 480B-A35B Instruct.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.

## Snapshot

| | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 33.4 | 38.1 |
| Rank | 243 | 190 |
| Context | 262K | 262K |
| Input $/M | $0.15 | $1.50 |
| Output $/M | $0.60 | $7.50 |
| Weights | Open | Open |

## Coding

- Mistral Small: 34.0 (#247)
- Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Coding | 1362 | 1412 |
| ALE-Bench | 497.62 | 461.45 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| SciCode | 26.5% | — |
| GSO | — | 4.9% |
| WeirdML | — | 41.2% |
| BigCodeBench Instruct | 36.1% | — |
| LiveBench Coding | 36.2% | — |
| BigCodeBench Complete | 46.6% | — |
| AlgoTune | — | 1.44 |

## Agentic & Tool Use

- Mistral Small: 28.1 (#93)
- Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| Berkeley Function Calling Leaderboard | 37.1% | — |

## Reasoning

- Mistral Small: 19.8 (#250)
- Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 37.8% | 49.5% |
| LMArena Hard Prompts | 1335 | 1372 |
| CritPt | 0% | — |
| LiveBench Reasoning | 44.8% | — |
| DTBench | 70.9% | — |
| LiveBench Data Analysis | 53.7% | — |
| LMCA | 20.6% | — |
| LiveBench | 44% | — |

## Math

- Mistral Small: 16.4 (#293)
- Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1341 | 1365 |
| OTIS Mock AIME 2024-2025 | 5.8% | — |
| LiveBench Math | 39.9% | — |
| MATH Level 5 | 46.8% | — |

## Knowledge

- Mistral Small: 31.0 (#222)
- Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1291 | 1338 |
| GPQA Diamond | 47.5% | — |
| Vectara Hallucination Rate | 5.1% | — |
| MMLU | 68.7% | — |

## Multimodal

- Mistral Small: 33.5 (#96)
- Qwen3-Coder 480B-A35B Instruct: —

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1142 | — |

## Multilingual

- Mistral Small: 45.5 (#169)
- Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1315 | 1346 |
| LMArena Chinese | 1340 | 1357 |
| LMArena French | 1337 | 1398 |
| LMArena German | 1340 | 1325 |
| LMArena Japanese | 1275 | 1310 |
| LMArena Korean | 1259 | 1305 |
| LMArena Russian | 1324 | 1366 |
| LMArena Spanish | 1346 | 1360 |

## Instruction Following

- Mistral Small: 66.4 (#209)
- Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1310 | 1355 |
| LiveBench Instruction Following | 63.7% | — |

## Long Context

- Mistral Small: 40.4 (#156)
- Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1327 | 1378 |

## Writing & Preference

- Mistral Small: 52.5 (#171)
- Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)

| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1338 | 1357 |
| LMArena Creative Writing | 1305 | 1333 |
| LMArena Multi-Turn | 1344 | 1365 |
| LiveBench Language | 30.5% | — |

## FAQ

### Is Mistral Small better than Qwen3-Coder 480B-A35B Instruct?

Qwen3-Coder 480B-A35B Instruct is the stronger model overall, scoring 38.1 to 33.4 on the Noometry Index. Mistral Small costs 11× less per token, which makes it the better buy when Qwen3-Coder 480B-A35B Instruct's lead doesn't matter for your workload.

### Which is cheaper, Mistral Small or Qwen3-Coder 480B-A35B Instruct?

Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.

### Is Mistral Small or Qwen3-Coder 480B-A35B Instruct better for coding?

Qwen3-Coder 480B-A35B Instruct scores higher on coding benchmarks: 35.5 versus 34.0 in the Noometry coding category.

### Which has the bigger context window?

Both accept 262K tokens.

### How many benchmarks do Mistral Small and Qwen3-Coder 480B-A35B Instruct share?

19 benchmarks have published results for both models. Mistral Small has 39 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.