Model comparison
Mistral Small 3.1 vs Qwen3.5 27B
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 2.1× less per token, which makes it the better buy when Qwen3.5 27B's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. Mistral Small 3.1 scores higher in 0 categories and Qwen3.5 27B in 9 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.5 27B leads 38.8 to 14.7.
- Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $0.30 / $2.40 for Qwen3.5 27B.
- Qwen3.5 27B accepts more context: 262K tokens versus 128K.
Side by side
| Mistral Small 3.1 | Qwen3.5 27B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 31.7 | 41.9 |
| Released | 2025-03-17 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 102K | 66K |
| Input $ / M tokens | $0.35 | $0.30 |
| Output $ / M tokens | $0.56 | $2.40 |
| Results tracked | 28 | 28 |
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Category by category
Coding Too close to call
Mistral Small 3.1: 38.3 (#179), Qwen3.5 27B: 38.9 (#168)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Coding | 1309 | 1427 |
| LMArena WebDev | — | 1358 |
| WeirdML | — | 39.5% |
| ALE-Bench | — | 349.45 |
Agentic & Tool Use Not comparable
Mistral Small 3.1: —, Qwen3.5 27B: —
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| Vending-Bench 2 | — | 201.98 |
Reasoning Qwen3.5 27B leads
Mistral Small 3.1: 19.7 (#254), Qwen3.5 27B: 27.5 (#117)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Hard Prompts | 1278 | 1414 |
| NYT Connections (extended) | — | 47.9% |
| Chess Puzzles | 1% | — |
| Thematic Generalization | — | 45.5% |
| DTBench | — | 82.4% |
| LMCA | — | 34% |
| Epoch Capabilities Index | 127.48 | — |
Math Qwen3.5 27B leads
Mistral Small 3.1: 14.7 (#301), Qwen3.5 27B: 38.8 (#127)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Math | 1262 | 1429 |
| MathArena Final-Answer Competitions | — | 56.7% |
| OTIS Mock AIME 2024-2025 | 3.9% | — |
| Omni-MATH | 24.8% | — |
Knowledge Qwen3.5 27B leads
Mistral Small 3.1: 22.6 (#271), Qwen3.5 27B: 38.0 (#150)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Expert | 1257 | 1428 |
| GPQA Diamond | 41.9% | — |
| MMLU-Pro | 61% | — |
| Vectara Hallucination Rate | — | 12.1% |
| GPQA (HELM) | 39.2% | — |
Multimodal Qwen3.5 27B leads
Mistral Small 3.1: 33.2 (#99), Qwen3.5 27B: 39.4 (#59)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | 1136 | 1241 |
Multilingual Qwen3.5 27B leads
Mistral Small 3.1: 41.2 (#209), Qwen3.5 27B: 50.8 (#115)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | 1255 | 1390 |
| LMArena Chinese | 1253 | 1478 |
| LMArena French | 1273 | 1410 |
| LMArena German | 1266 | 1393 |
| LMArena Japanese | 1208 | 1345 |
| LMArena Korean | 1206 | 1358 |
| LMArena Russian | 1263 | 1390 |
| LMArena Spanish | 1283 | 1407 |
Instruction Following Qwen3.5 27B leads
Mistral Small 3.1: 63.6 (#230), Qwen3.5 27B: 73.5 (#119)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | 1264 | 1393 |
| IFEval | 75% | — |
Long Context Qwen3.5 27B leads
Mistral Small 3.1: 39.5 (#178), Qwen3.5 27B: 43.1 (#106)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | 1299 | 1413 |
Writing & Preference Qwen3.5 27B leads
Mistral Small 3.1: 37.0 (#259), Qwen3.5 27B: 59.3 (#111)
| Benchmark | Mistral Small 3.1 | Qwen3.5 27B |
|---|---|---|
| LMArena Text | 1277 | 1409 |
| LMArena Creative Writing | 1253 | 1362 |
| LMArena Multi-Turn | 1270 | 1410 |
| EQ-Bench Creative Writing | 761 | — |
| WildBench | 78.8% | — |
Frequently asked questions
Is Mistral Small 3.1 better than Qwen3.5 27B?
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 2.1× less per token, which makes it the better buy when Qwen3.5 27B's lead doesn't matter for your workload.
Which is cheaper, Mistral Small 3.1 or Qwen3.5 27B?
Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; Qwen3.5 27B lists at $0.30 and $2.40.
Is Mistral Small 3.1 or Qwen3.5 27B better for coding?
They score almost the same on coding (38.3 vs 38.9); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3.5 27B does, with 262K tokens against 128K.
How many benchmarks do Mistral Small 3.1 and Qwen3.5 27B share?
18 benchmarks have published results for both models. Mistral Small 3.1 has 28 scored results on Noometry and Qwen3.5 27B has 28.