Model comparison
Mistral Medium vs Qwen3-VL 235B-A22B
Qwen3-VL 235B-A22B is the stronger model overall, scoring 42.5 to 36.0 on the Noometry Index.
Last verified . 18 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. Mistral Medium scores higher in 1 category and Qwen3-VL 235B-A22B in 8 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3-VL 235B-A22B leads 39.6 to 24.9.
- Qwen3-VL 235B-A22B is cheaper at $0.70 / $2.80 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium.
- Mistral Medium accepts more context: 262K tokens versus 131K.
Side by side
| Mistral Medium | Qwen3-VL 235B-A22B | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 36.0 | 42.5 |
| Released | 2023-12-11 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 262K | 33K |
| Input $ / M tokens | $1.50 | $0.70 |
| Output $ / M tokens | $7.50 | $2.80 |
| Results tracked | 36 | 18 |
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Category by category
Coding Qwen3-VL 235B-A22B leads
Mistral Medium: 33.8 (#241), Qwen3-VL 235B-A22B: 41.8 (#103)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Coding | 1434 | 1438 |
| FrontierCode | 8% | — |
| SciCode | 40.2% | — |
| WeirdML | 43.7% | — |
| ALE-Bench | 763.98 | — |
Agentic & Tool Use Not comparable
Mistral Medium: 28.1 (#84), Qwen3-VL 235B-A22B: —
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.7% | — |
Reasoning Qwen3-VL 235B-A22B leads
Mistral Medium: 23.3 (#165), Qwen3-VL 235B-A22B: 28.1 (#92)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1428 |
| Kagi LLM Benchmark | 50% | — |
| CritPt | 0% | — |
| DTBench | 75.5% | — |
| LMCA | 26.1% | — |
| Surface Evolver Bench | 26.9% | — |
Math Qwen3-VL 235B-A22B leads
Mistral Medium: 27.2 (#238), Qwen3-VL 235B-A22B: 36.2 (#120)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Math | 1409 | 1426 |
| OTIS Mock AIME 2024-2025 | 32.2% | — |
| ProofBench | 9% | — |
| MATH Level 5 | 81.6% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge Qwen3-VL 235B-A22B leads
Mistral Medium: 24.9 (#260), Qwen3-VL 235B-A22B: 39.6 (#120)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Expert | 1408 | 1440 |
| GPQA Diamond | 59.5% | — |
| Humanity's Last Exam | 4.5% | — |
| Vectara Hallucination Rate | 22.7% | — |
Multimodal Qwen3-VL 235B-A22B leads
Mistral Medium: 34.6 (#82), Qwen3-VL 235B-A22B: 39.1 (#50)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Vision | 1172 | 1247 |
Multilingual Too close to call
Mistral Medium: 52.3 (#86), Qwen3-VL 235B-A22B: 52.1 (#92)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Non-English | 1408 | 1405 |
| LMArena Chinese | 1448 | 1462 |
| LMArena French | 1460 | 1448 |
| LMArena German | 1433 | 1424 |
| LMArena Japanese | 1378 | 1385 |
| LMArena Korean | 1382 | 1395 |
| LMArena Russian | 1411 | 1409 |
| LMArena Spanish | 1433 | 1427 |
Instruction Following Too close to call
Mistral Medium: 73.9 (#111), Qwen3-VL 235B-A22B: 74.4 (#95)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Instruction Following | 1398 | 1407 |
Long Context Too close to call
Mistral Medium: 42.9 (#108), Qwen3-VL 235B-A22B: 43.4 (#93)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Longer Query | 1406 | 1420 |
Writing & Preference Too close to call
Mistral Medium: 60.2 (#97), Qwen3-VL 235B-A22B: 60.4 (#94)
| Benchmark | Mistral Medium | Qwen3-VL 235B-A22B |
|---|---|---|
| LMArena Text | 1424 | 1420 |
| LMArena Creative Writing | 1391 | 1367 |
| LMArena Multi-Turn | 1418 | 1428 |
| Short-Story Creative Writing | 77.3% | — |
Frequently asked questions
Is Mistral Medium better than Qwen3-VL 235B-A22B?
Qwen3-VL 235B-A22B is the stronger model overall, scoring 42.5 to 36.0 on the Noometry Index.
Which is cheaper, Mistral Medium or Qwen3-VL 235B-A22B?
Qwen3-VL 235B-A22B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; Mistral Medium lists at $1.50 and $7.50.
Is Mistral Medium or Qwen3-VL 235B-A22B better for coding?
Qwen3-VL 235B-A22B scores higher on coding benchmarks: 41.8 versus 33.8 in the Noometry coding category.
Which has the bigger context window?
Mistral Medium does, with 262K tokens against 131K.
How many benchmarks do Mistral Medium and Qwen3-VL 235B-A22B share?
18 benchmarks have published results for both models. Mistral Medium has 36 scored results on Noometry and Qwen3-VL 235B-A22B has 18.