Mistral Medium 3 vs Qwen2.5 VL 72B Instruct
Qwen2.5 VL 72B Instruct costs 2.0x less per output token than Mistral Medium 3 ($1.00 vs $2.00 per million). Updated October 21, 2026; 3 benchmarks have a result for both.
Mistral Medium 3 or Qwen2.5 VL 72B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Medium 3 for a larger context window (131K against 128K tokens).
- Shared results
- 3
- Mistral Medium 3 only
- 54
- Qwen2.5 VL 72B Instruct only
- 3
- Like-for-like categories
- 1 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Mistral Medium 3 has a AA Intelligence Index result, 9.0.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Medium 3 has a Design Arena: websites result, 1079.
Directional only
Long documents
Listed context window
Mistral Medium 3
Mistral Medium 3 takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 VL 72B Instruct
Mistral Medium 3 $0.0014, Qwen2.5 VL 72B Instruct $0.0013 per turn.
List prices
At a glance
- Coding index
- Mistral Medium 3 not benchmarked, Qwen2.5 VL 72B Instruct not benchmarked.
- Widest category
- General, 8.9 points apart on average over 3 shared benchmarks.
- Widest single gap
- LMArena Vision: English: Mistral Medium 3 1172 against Qwen2.5 VL 72B Instruct 1115, 9.5 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3 $2.00 against Qwen2.5 VL 72B Instruct $1.00 per million output tokens, 2.0x apart.
- Context window
- Mistral Medium 3 takes 131K tokens, Qwen2.5 VL 72B Instruct 128K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Mistral Medium 3 | Bars | Qwen2.5 VL 72B Instruct | Ties |
|---|---|---|---|---|
| General | 3 | 0 | ||
| All shared boards | 3 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 40.0% | Not measured | Only Mistral Medium 3 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 3.8% | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: coding | 1385 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: software and IT | 1385 | Not measured | Only Mistral Medium 3 measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.0 | Not measured | Only Mistral Medium 3 measured |
| Epoch Capabilities Index | 134.0 | Not measured | Only Mistral Medium 3 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 24.3% | Not measured | Only Mistral Medium 3 measured |
| OSWorld | Not measured | 5.0% | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 57.8% | Not measured | Only Mistral Medium 3 measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.1% | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: hard prompts | 1364 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: expert | 1342 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: hard prompts in English | 1374 | Not measured | Only Mistral Medium 3 measured |
| LMArena Vision: diagrams | 1155 | Not measured | Only Mistral Medium 3 measured |
| LMArena Vision: homework | 1165 | Not measured | Only Mistral Medium 3 measured |
| Kagi LLM Benchmark | Not measured | 36.0% | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| AA Math Index | 30.3 | Not measured | Only Mistral Medium 3 measured |
| AIME 2025 (Artificial Analysis run) | 30.3% | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: math | 1353 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: mathematical work | 1354 | Not measured | Only Mistral Medium 3 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 76.0% | Not measured | Only Mistral Medium 3 measured |
| GeoBench | Not measured | 62.0% | Only Qwen2.5 VL 72B Instruct measured |
| LMArena Text: science | 1381 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: medicine and healthcare | 1381 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: legal and government | 1384 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: business and finance | 1352 | Not measured | Only Mistral Medium 3 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1079 | Not measured | Only Mistral Medium 3 measured |
| Design Arena: UI components | 1024 | Not measured | Only Mistral Medium 3 measured |
| Design Arena: game dev | 1018 | Not measured | Only Mistral Medium 3 measured |
| Design Arena: data viz | 1034 | Not measured | Only Mistral Medium 3 measured |
| Design Arena: 3D | 1084 | Not measured | Only Mistral Medium 3 measured |
| Design Arena: all code categories | 1069 | Not measured | Only Mistral Medium 3 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| IFBench | 39.3% | Not measured | Only Mistral Medium 3 measured |
| Long context reasoning (AA-LCR) | 31.3% | Not measured | Only Mistral Medium 3 measured |
| DTBench | 62.3% | Not measured | Only Mistral Medium 3 measured |
| LMArena Text | 1370 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: instruction following | 1338 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: creative writing | 1343 | Not measured | Only Mistral Medium 3 measured |
| LMArena Vision | 1157 | 1107 | Mistral Medium 3 |
| LMArena Text: English | 1385 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: non-English | 1353 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: Chinese | 1374 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: German | 1377 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: Japanese | 1316 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: Korean | 1304 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: French | 1368 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: Spanish | 1364 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: Russian | 1359 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: Polish | 1371 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: multi-turn | 1384 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: longer queries | 1360 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: writing and language | 1352 | Not measured | Only Mistral Medium 3 measured |
| LMArena Text: entertainment and media | 1335 | Not measured | Only Mistral Medium 3 measured |
| LMArena Vision: English | 1172 | 1115 | Mistral Medium 3 |
| LMArena Vision: Chinese | 1161 | 1107 | Mistral Medium 3 |
| LMArena Vision: reading text | 1154 | Not measured | Only Mistral Medium 3 measured |
| LMArena Vision: humor | 1145 | Not measured | Only Mistral Medium 3 measured |
| LMArena Vision: captioning | 1094 | Not measured | Only Mistral Medium 3 measured |
| LMArena Vision: recognizing things | 1141 | Not measured | Only Mistral Medium 3 measured |
| LMArena Vision: creative writing | 1146 | Not measured | Only Mistral Medium 3 measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Medium 3 | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen2.5 VL 72B Instruct costs less
Repository review
50K input + 3K output tokens
Mistral Medium 3 costs less
Agent loop
200K input + 10K output tokens
Mistral Medium 3 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Mistral Medium 3 | Qwen2.5 VL 72B Instruct |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | May 7, 2025 | February 1, 2025 |
| Context window | 131K | 128K |
| Input $/Mtok | $0.40 | $0.80 |
| Output $/Mtok | $2.00 | $1.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3 better than Qwen2.5 VL 72B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Medium 3 for a larger context window (131K against 128K tokens).
Which is cheaper, Mistral Medium 3 or Qwen2.5 VL 72B Instruct?
Mistral Medium 3 costs $0.40 per million input tokens and $2.00 per million output tokens; Qwen2.5 VL 72B Instruct costs $0.80 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Medium 3 or Qwen2.5 VL 72B Instruct?
Mistral Medium 3, with 131K tokens against 128K.
How many benchmarks is the Mistral Medium 3 vs Qwen2.5 VL 72B Instruct comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. Mistral Medium 3's coding index rests on 0 independent benchmarks and Qwen2.5 VL 72B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.