Model comparison
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.
Last verified . 19 shared benchmarks.
Mistral AI
Alibaba (Qwen)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.
Side by side
| Mistral Small | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 33.4 | 38.1 |
| Released | 2024-02-26 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 256K | 66K |
| Input $ / M tokens | $0.15 | $1.50 |
| Output $ / M tokens | $0.60 | $7.50 |
| Results tracked | 39 | 25 |
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Category by category
Coding Qwen3-Coder 480B-A35B Instruct leads
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 leads
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 Qwen3-Coder 480B-A35B Instruct leads
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 Qwen3-Coder 480B-A35B Instruct leads
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 Qwen3-Coder 480B-A35B Instruct leads
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 Not comparable
Mistral Small: 33.5 (#96), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | Mistral Small | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1142 | — |
Multilingual Qwen3-Coder 480B-A35B Instruct leads
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 Qwen3-Coder 480B-A35B Instruct leads
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 Qwen3-Coder 480B-A35B Instruct leads
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 Qwen3-Coder 480B-A35B Instruct leads
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% | — |
Frequently asked questions
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.