Mistral Medium 3.5 vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads Mistral Medium 3.5 on coding, 65.4 to 25.5 on the Vibe Coding Index, and MiMo-V2.6-Pro costs 8.6x less per output token ($0.87 vs $7.50 per million). Updated October 22, 2026; 52 benchmarks have a result for both.
Mistral Medium 3.5 or MiMo-V2.6-Pro: which to pick
Pick MiMo-V2.6-Pro for coding: it scores 65.4 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5.
Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 52
- Mistral Medium 3.5 only
- 29
- MiMo-V2.6-Pro only
- 21
- Like-for-like categories
- 8 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
MiMo-V2.6-Pro
MiMo-V2.6-Pro scores 65.4 against 25.5.
3 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 46.3 against 14.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.5 has a AA Agentic Index result, 7.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Medium 3.5 has a GPQA Diamond result, 34.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Medium 3.5 has a MMLU Pro result, 75.3%.
Directional only
Web design
Design Arena: websites
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 1308 against 1142.
Same board, both measured
General
Vals Index
No call
Only MiMo-V2.6-Pro has a Vals Index result, 57.8%.
Directional only
Long documents
Listed context window
MiMo-V2.6-Pro
MiMo-V2.6-Pro takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Pro
Mistral Medium 3.5 $0.0053, MiMo-V2.6-Pro $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Medium 3.5 has the number, $6.02.
Directional only
At a glance
- Coding index
- Mistral Medium 3.5 25.5 from 3 benchmarks, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Coding, 36.5 points apart on average over 10 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Mistral Medium 3.5 2.9% against MiMo-V2.6-Pro 85.2%, 82.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.5 $7.50 against MiMo-V2.6-Pro $0.87 per million output tokens, 8.6x apart.
- Context window
- Mistral Medium 3.5 takes 262K tokens, MiMo-V2.6-Pro 1.05M.
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 3.5 | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 10 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 4 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 5 | ||
| Web design | 0 | 6 | ||
| General | 0 | 17 | ||
| All shared boards | 0 | 52 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index010
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 81.5% | Only MiMo-V2.6-Pro measured |
| LMArena WebDev | 1264 | 1625 | MiMo-V2.6-Pro |
| AA Coding Index | 46.9 | Not measured | Only Mistral Medium 3.5 measured |
| SWE-bench Verified (Vals AI) | 66.4% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.3% | Only MiMo-V2.6-Pro measured |
| Vibe Code Bench (Vals AI) | 2.9% | 85.2% | MiMo-V2.6-Pro |
| Code migration (Vals AI) | 5.1% | 43.0% | MiMo-V2.6-Pro |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only MiMo-V2.6-Pro measured |
| IOI (Vals AI) | Not measured | 39.3% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench 2.1 (Vals AI) | 39.0% | 67.8% | MiMo-V2.6-Pro |
| SWE-bench Multimodal (Vals AI) | Not measured | 41.3% | Only MiMo-V2.6-Pro measured |
| CyberBench (Vals AI) | Not measured | 72.9% | Only MiMo-V2.6-Pro measured |
| SciCode | 40.2% | 60.9% | MiMo-V2.6-Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only Mistral Medium 3.5 measured |
| ALE-Bench | 764.0 | 1158.1 | MiMo-V2.6-Pro |
| LMArena Text: coding | 1460 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1458 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | 1254 | 1639 | MiMo-V2.6-Pro |
| LMArena WebDev: HTML | 1308 | 1616 | MiMo-V2.6-Pro |
| LMArena WebDev: from an image | Not measured | 1598 | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.2 | 46.3 | MiMo-V2.6-Pro |
| Epoch Capabilities Index | 141.4 | Not measured | Only Mistral Medium 3.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 7.0 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: agents building web apps | Not measured | 1290 | Only MiMo-V2.6-Pro measured |
| LiveBench research | Not measured | 76.7% | Only MiMo-V2.6-Pro measured |
| LiveBench browser | Not measured | 88.0% | Only MiMo-V2.6-Pro measured |
| LiveBench long agentic | Not measured | 47.5% | Only MiMo-V2.6-Pro measured |
| SREBench (Vals AI) | Not measured | 3.0% | Only MiMo-V2.6-Pro measured |
| Finance Agent (Vals AI) | 32.1% | 57.3% | MiMo-V2.6-Pro |
| Tax Agent Bench (Vals AI) | 4.5% | 32.4% | MiMo-V2.6-Pro |
| Legal Research Bench (Vals AI) | 9.1% | 47.1% | MiMo-V2.6-Pro |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 13.8% | Only MiMo-V2.6-Pro measured |
| Excel Modeling Benchmark (Vals AI) | 11.2% | 62.9% | MiMo-V2.6-Pro |
| Terminal-Bench-Science (Vals AI) | Not measured | 2.9% | Only MiMo-V2.6-Pro measured |
| τ²-Bench Telecom | 94.2% | Not measured | Only Mistral Medium 3.5 measured |
| APEX-Agents | Not measured | 54.4% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 34.9% | Not measured | Only Mistral Medium 3.5 measured |
| LiveBench reasoning | Not measured | 79.6% | Only MiMo-V2.6-Pro measured |
| MysteryMechanism (Vals AI) | Not measured | 15.3% | Only MiMo-V2.6-Pro measured |
| GPQA Diamond (Artificial Analysis run) | 74.8% | Not measured | Only Mistral Medium 3.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | 13.8% | 49.4% | MiMo-V2.6-Pro |
| LMArena Text: hard prompts | 1436 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1432 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1445 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1254 | 1281 | MiMo-V2.6-Pro |
| LMArena Vision: homework | 1230 | 1264 | MiMo-V2.6-Pro |
| Kagi LLM Benchmark | 41.4% | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| ProofBench | 9.0% | 70.0% | MiMo-V2.6-Pro |
| LMArena Text: math | 1431 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1440 | 1511 | MiMo-V2.6-Pro |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MMLU Pro | 75.3% | Not measured | Only Mistral Medium 3.5 measured |
| CaseLaw (Vals AI) | 44.2% | Not measured | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | 58.8% | Not measured | Only Mistral Medium 3.5 measured |
| TaxEval (Vals AI) | 68.0% | Not measured | Only Mistral Medium 3.5 measured |
| MortgageTax (Vals AI) | 28.9% | Not measured | Only Mistral Medium 3.5 measured |
| MedCode (Vals AI) | 33.8% | 45.0% | MiMo-V2.6-Pro |
| LMArena Text: science | 1428 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1409 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1437 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1426 | 1468 | MiMo-V2.6-Pro |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1142 | 1308 | MiMo-V2.6-Pro |
| Design Arena: UI components | 1076 | 1340 | MiMo-V2.6-Pro |
| Design Arena: game dev | 1079 | 1314 | MiMo-V2.6-Pro |
| Design Arena: data viz | 1120 | 1336 | MiMo-V2.6-Pro |
| Design Arena: 3D | 1060 | 1330 | MiMo-V2.6-Pro |
| Design Arena: all code categories | 1121 | 1317 | MiMo-V2.6-Pro |
| Design Arena: SVG | 949 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | 1062 | Not measured | Only Mistral Medium 3.5 measured |
| LiveBench design | Not measured | 78.5% | Only MiMo-V2.6-Pro measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 57.8% | Only MiMo-V2.6-Pro measured |
| LiveBench data analysis | Not measured | 72.3% | Only MiMo-V2.6-Pro measured |
| Public Benefits Bench (Vals AI) | Not measured | 68.9% | Only MiMo-V2.6-Pro measured |
| SAGE (Vals AI) | 37.6% | 45.0% | MiMo-V2.6-Pro |
| MedScribe (Vals AI) | 67.7% | 88.3% | MiMo-V2.6-Pro |
| Vals Multimodal Index | 34.8% | Not measured | Only Mistral Medium 3.5 measured |
| IFBench | 68.8% | Not measured | Only Mistral Medium 3.5 measured |
| Long context reasoning (AA-LCR) | 69.3% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 75.5% | Not measured | Only Mistral Medium 3.5 measured |
| LMCA | 26.1% | Not measured | Only Mistral Medium 3.5 measured |
| Surface Evolver Bench | 26.9% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text | 1421 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1415 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1374 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1222 | 1263 | MiMo-V2.6-Pro |
| LMArena Text: English | 1433 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1404 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1444 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: German | 1453 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Korean | 1384 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: French | 1448 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Spanish | 1411 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Russian | 1395 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: Polish | 1430 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: multi-turn | 1423 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1415 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1384 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1382 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1240 | 1268 | MiMo-V2.6-Pro |
| LMArena Vision: Chinese | 1244 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: reading text | 1233 | 1270 | MiMo-V2.6-Pro |
| LMArena Vision: humor | 1216 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: creative writing | 1198 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Medium 3.5 | MiMo-V2.6-Pro | 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
MiMo-V2.6-Pro costs less
Repository review
50K input + 3K output tokens
MiMo-V2.6-Pro costs less
Agent loop
200K input + 10K output tokens
MiMo-V2.6-Pro 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 3.5 | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Mistral AI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | April 30, 2026 | September 21, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $1.50 | $0.435 |
| Output $/Mtok | $7.50 | $0.87 |
| Coding index | 25.5 | 65.4 |
| Independent measurements behind it | 3 | 4 |
| Cost per solved task | $6.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.5 better than MiMo-V2.6-Pro for coding?
Pick MiMo-V2.6-Pro for coding: it scores 65.4 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5. Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, Mistral Medium 3.5 or MiMo-V2.6-Pro?
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; MiMo-V2.6-Pro costs $0.435 and $0.87. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, Mistral Medium 3.5 or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 262K.
How many benchmarks is the Mistral Medium 3.5 vs MiMo-V2.6-Pro comparison based on?
52 benchmarks have a result for both models as of October 22, 2026. Mistral Medium 3.5's coding index rests on 3 independent benchmarks and MiMo-V2.6-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.