Model comparison
Mistral Small vs Qwen3-VL 235B-A22B
Qwen3-VL 235B-A22B is the stronger model overall, scoring 43.2 to 33.4 on the Noometry Index. Mistral Small costs 4.7× less per token, which makes it the better buy when Qwen3-VL 235B-A22B's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. Mistral Small scores higher in 0 categories and Qwen3-VL 235B-A22B in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-VL 235B-A22B leads 39.0 to 16.4.
- Mistral Small is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.70 / $2.80 for Qwen3-VL 235B-A22B.
- Mistral Small accepts more context: 262K tokens versus 131K.
Side by side
| Mistral Small | Qwen3-VL 235B-A22B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 33.4 | 43.2 |
| Released | 2024-02-26 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 256K | 33K |
| Input $ / M tokens | $0.15 | $0.70 |
| Output $ / M tokens | $0.60 | $2.80 |
| Results tracked | 39 | 18 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Qwen3-VL 235B-A22B leads
Mistral Small: 34.0 (#247), Qwen3-VL 235B-A22B: 42.4 (#100)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Coding | 1362 | 1439 |
| SciCode | 26.5% | — |
| BigCodeBench Instruct | 36.1% | — |
| LiveBench Coding | 36.2% | — |
| BigCodeBench Complete | 46.6% | — |
| ALE-Bench | 497.62 | — |
Agentic & Tool Use Not comparable
Mistral Small: 28.1 (#93), Qwen3-VL 235B-A22B: —
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.1% | — |
Reasoning Qwen3-VL 235B-A22B leads
Mistral Small: 19.8 (#250), Qwen3-VL 235B-A22B: 29.3 (#92)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Hard Prompts | 1335 | 1428 |
| Kagi LLM Benchmark | 37.8% | — |
| CritPt | 0% | — |
| LiveBench Reasoning | 44.8% | — |
| DTBench | 70.9% | — |
| LiveBench Data Analysis | 53.7% | — |
| LMCA | 20.6% | — |
| LiveBench | 44% | — |
Math Qwen3-VL 235B-A22B leads
Mistral Small: 16.4 (#293), Qwen3-VL 235B-A22B: 39.0 (#118)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Math | 1341 | 1426 |
| OTIS Mock AIME 2024-2025 | 5.8% | — |
| LiveBench Math | 39.9% | — |
| MATH Level 5 | 46.8% | — |
Knowledge Qwen3-VL 235B-A22B leads
Mistral Small: 31.0 (#222), Qwen3-VL 235B-A22B: 40.3 (#121)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Expert | 1291 | 1442 |
| GPQA Diamond | 47.5% | — |
| Vectara Hallucination Rate | 5.1% | — |
| MMLU | 68.7% | — |
Multimodal Qwen3-VL 235B-A22B leads
Mistral Small: 33.5 (#96), Qwen3-VL 235B-A22B: 39.8 (#55)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Vision | 1142 | 1247 |
Multilingual Qwen3-VL 235B-A22B leads
Mistral Small: 45.5 (#169), Qwen3-VL 235B-A22B: 51.9 (#97)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Non-English | 1315 | 1405 |
| LMArena Chinese | 1340 | 1463 |
| LMArena French | 1337 | 1452 |
| LMArena German | 1340 | 1424 |
| LMArena Japanese | 1275 | 1385 |
| LMArena Korean | 1259 | 1394 |
| LMArena Russian | 1324 | 1408 |
| LMArena Spanish | 1346 | 1428 |
Instruction Following Qwen3-VL 235B-A22B leads
Mistral Small: 66.4 (#209), Qwen3-VL 235B-A22B: 74.2 (#101)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Instruction Following | 1310 | 1406 |
| LiveBench Instruction Following | 63.7% | — |
Long Context Qwen3-VL 235B-A22B leads
Mistral Small: 40.4 (#156), Qwen3-VL 235B-A22B: 43.4 (#98)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Longer Query | 1327 | 1420 |
Writing & Preference Qwen3-VL 235B-A22B leads
Mistral Small: 52.5 (#171), Qwen3-VL 235B-A22B: 60.2 (#99)
| Benchmark | Mistral Small | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Text | 1338 | 1420 |
| LMArena Creative Writing | 1305 | 1366 |
| LMArena Multi-Turn | 1344 | 1428 |
| LiveBench Language | 30.5% | — |
Frequently asked questions
Is Mistral Small better than Qwen3-VL 235B-A22B?
Qwen3-VL 235B-A22B is the stronger model overall, scoring 43.2 to 33.4 on the Noometry Index. Mistral Small costs 4.7× less per token, which makes it the better buy when Qwen3-VL 235B-A22B's lead doesn't matter for your workload.
Which is cheaper, Mistral Small or Qwen3-VL 235B-A22B?
Mistral Small is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Qwen3-VL 235B-A22B lists at $0.70 and $2.80.
Is Mistral Small or Qwen3-VL 235B-A22B better for coding?
Qwen3-VL 235B-A22B scores higher on coding benchmarks: 42.4 versus 34.0 in the Noometry coding category.
Which has the bigger context window?
Mistral Small does, with 262K tokens against 131K.
How many benchmarks do Mistral Small and Qwen3-VL 235B-A22B share?
18 benchmarks have published results for both models. Mistral Small has 39 scored results on Noometry and Qwen3-VL 235B-A22B has 18.