Model comparison
Mistral Medium vs Qwen2.5-VL 72B Instruct
Mistral Medium is the stronger model overall, scoring 36.3 to 29.9 on the Noometry Index.
Last verified . 2 shared benchmarks.
Mistral AI
Alibaba (Qwen)Summary
- They share 2 benchmarks with published results for both. Mistral Medium scores higher in 3 categories and Qwen2.5-VL 72B Instruct in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Mistral Medium leads 28.3 to 18.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 50% for Mistral Medium and 36% for Qwen2.5-VL 72B Instruct.
- Mistral Medium is cheaper at $1.50 / $7.50 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
- Mistral Medium accepts more context: 262K tokens versus 131K.
Side by side
| Mistral Medium | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 36.3 | 29.9 |
| Released | 2023-12-11 | 2024-09 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 262K | 8K |
| Input $ / M tokens | $1.50 | $2.80 |
| Output $ / M tokens | $7.50 | $8.40 |
| Results tracked | 36 | 6 |
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Category by category
Coding Not comparable
Mistral Medium: 34.2 (#243), Qwen2.5-VL 72B Instruct: —
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| FrontierCode | 8% | — |
| SciCode | 40.2% | — |
| WeirdML | 43.7% | — |
| LMArena Coding | 1434 | — |
| ALE-Bench | 763.98 | — |
Agentic & Tool Use Mistral Medium leads
Mistral Medium: 28.3 (#90), Qwen2.5-VL 72B Instruct: 18.6 (#144)
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 37.7% | — |
| OSWorld | — | 5% |
Reasoning Mistral Medium leads
Mistral Medium: 24.0 (#167), Qwen2.5-VL 72B Instruct: 20.7 (#233)
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 50% | 36% |
| CritPt | 0% | — |
| LMArena Hard Prompts | 1426 | — |
| DTBench | 75.5% | — |
| LMCA | 26.1% | — |
| Surface Evolver Bench | 26.9% | — |
Math Not comparable
Mistral Medium: 28.1 (#245), Qwen2.5-VL 72B Instruct: —
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 32.2% | — |
| ProofBench | 9% | — |
| LMArena Math | 1408 | — |
| MATH Level 5 | 81.6% | — |
| FrontierMath (Feb 2025 set) | 0.3% | — |
Knowledge Not comparable
Mistral Medium: 25.0 (#265), Qwen2.5-VL 72B Instruct: —
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| GPQA Diamond | 59.5% | — |
| Humanity's Last Exam | 4.5% | — |
| Vectara Hallucination Rate | 22.7% | — |
| LMArena Expert | 1408 | — |
Multimodal Mistral Medium leads
Mistral Medium: 35.3 (#88), Qwen2.5-VL 72B Instruct: 33.5 (#97)
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | 1172 | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
Mistral Medium: 52.1 (#91), Qwen2.5-VL 72B Instruct: —
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1408 | — |
| LMArena Chinese | 1447 | — |
| LMArena French | 1459 | — |
| LMArena German | 1432 | — |
| LMArena Japanese | 1378 | — |
| LMArena Korean | 1380 | — |
| LMArena Russian | 1411 | — |
| LMArena Spanish | 1433 | — |
Instruction Following Not comparable
Mistral Medium: 73.7 (#116), Qwen2.5-VL 72B Instruct: —
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1398 | — |
Long Context Not comparable
Mistral Medium: 42.9 (#114), Qwen2.5-VL 72B Instruct: —
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1406 | — |
Writing & Preference Not comparable
Mistral Medium: 60.0 (#103), Qwen2.5-VL 72B Instruct: —
| Benchmark | Mistral Medium | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1424 | — |
| LMArena Creative Writing | 1391 | — |
| Short-Story Creative Writing | 77.3% | — |
| LMArena Multi-Turn | 1418 | — |
Frequently asked questions
Is Mistral Medium better than Qwen2.5-VL 72B Instruct?
Mistral Medium is the stronger model overall, scoring 36.3 to 29.9 on the Noometry Index.
Which is cheaper, Mistral Medium or Qwen2.5-VL 72B Instruct?
Mistral Medium is cheaper. It lists at $1.50 per million input tokens and $7.50 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.
Which has the bigger context window?
Mistral Medium does, with 262K tokens against 131K.
How many benchmarks do Mistral Medium and Qwen2.5-VL 72B Instruct share?
2 benchmarks have published results for both models. Mistral Medium has 36 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.