Mistral Large 4 vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads Mistral Large 4 on coding, 65.4 to 56.4 on the Vibe Coding Index, and MiMo-V2.6-Pro costs 4.8x less per output token ($0.87 vs $4.18 per million). Updated October 22, 2026; 61 benchmarks have a result for both.
Mistral Large 4 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 56.4 for Mistral Large 4, though on 4 benchmarks against 5.
Pick Mistral Large 4 for work measured by IOI (Vals AI) or ALE-Bench, where it leads.
- Shared results
- 61
- Mistral Large 4 only
- 20
- MiMo-V2.6-Pro only
- 12
- 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 56.4.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 46.3 against 38.4.
Same board, both measured
Web design
Design Arena: websites
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 1308 against 1257.
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 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Pro
Mistral Large 4 $0.0034, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- Mistral Large 4 56.4 from 5 benchmarks, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Math, 24.5 points apart on average over 3 shared benchmarks.
- Widest single gap
- LiveBench browser: Mistral Large 4 8.0% against MiMo-V2.6-Pro 88.0%, 80.0 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against MiMo-V2.6-Pro $0.87 per million output tokens, 4.8x apart.
- Context window
- Mistral Large 4 takes 1.05M 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 Large 4 | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 2 | 11 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 7 | ||
| Reasoning | 2 | 5 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 5 | ||
| Web design | 0 | 7 | ||
| General | 4 | 13 | ||
| All shared boards | 9 | 52 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index211
| Benchmark | Mistral Large 4 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | 60.0% | 81.5% | MiMo-V2.6-Pro |
| LMArena WebDev | 1543 | 1625 | MiMo-V2.6-Pro |
| Terminal-Bench 4 (Vals AI) | 27.8% | 31.3% | MiMo-V2.6-Pro |
| Vibe Code Bench (Vals AI) | 78.4% | 85.2% | MiMo-V2.6-Pro |
| Code migration (Vals AI) | 30.6% | 43.0% | MiMo-V2.6-Pro |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only MiMo-V2.6-Pro measured |
| IOI (Vals AI) | 45.3% | 39.3% | Mistral Large 4 |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.8% | Only MiMo-V2.6-Pro measured |
| SWE-bench Multimodal (Vals AI) | 33.1% | 41.3% | MiMo-V2.6-Pro |
| Vibe Code Bench 1-100 (Vals AI) | 14.3% | Not measured | Only Mistral Large 4 measured |
| CyberBench (Vals AI) | Not measured | 72.9% | Only MiMo-V2.6-Pro measured |
| SciCode | 54.2% | 60.9% | MiMo-V2.6-Pro |
| FrontierCode | 39.4% | Not measured | Only Mistral Large 4 measured |
| ALE-Bench | 1213.2 | 1158.1 | Mistral Large 4 |
| LMArena Text: coding | 1478 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1467 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | 1559 | 1639 | MiMo-V2.6-Pro |
| LMArena WebDev: HTML | 1487 | 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 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 4 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 46.3 | MiMo-V2.6-Pro |
| Epoch Capabilities Index | 150.0 | Not measured | Only Mistral Large 4 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index17
| Benchmark | Mistral Large 4 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1290 | Only MiMo-V2.6-Pro measured |
| LiveBench research | 28.1% | 76.7% | MiMo-V2.6-Pro |
| LiveBench browser | 8.0% | 88.0% | MiMo-V2.6-Pro |
| LiveBench long agentic | 11.8% | 47.5% | MiMo-V2.6-Pro |
| SREBench (Vals AI) | Not measured | 3.0% | Only MiMo-V2.6-Pro measured |
| Finance Agent (Vals AI) | 54.7% | 57.3% | MiMo-V2.6-Pro |
| Tax Agent Bench (Vals AI) | 30.4% | 32.4% | MiMo-V2.6-Pro |
| Legal Research Bench (Vals AI) | 31.7% | 47.1% | MiMo-V2.6-Pro |
| Harvey's Legal Agent Benchmark (Vals AI) | 17.5% | 13.8% | Mistral Large 4 |
| Excel Modeling Benchmark (Vals AI) | 56.2% | 62.9% | MiMo-V2.6-Pro |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Mistral Large 4 measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 2.9% | Only MiMo-V2.6-Pro measured |
| APEX-Agents | Not measured | 54.4% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index25
| Benchmark | Mistral Large 4 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench reasoning | 83.9% | 79.6% | Mistral Large 4 |
| MysteryMechanism (Vals AI) | 12.2% | 15.3% | MiMo-V2.6-Pro |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | 49.4% | MiMo-V2.6-Pro |
| GPQA Diamond (Epoch AI run) | 88.1% | Not measured | Only Mistral Large 4 measured |
| Chess puzzles | 33.0% | Not measured | Only Mistral Large 4 measured |
| Mystery game puzzles | 17.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | 1444 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1444 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1442 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1288 | 1281 | Mistral Large 4 |
| LMArena Vision: homework | Not measured | 1264 | Only MiMo-V2.6-Pro 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 Large 4 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | Not measured | Only Mistral Large 4 measured |
| FrontierMath, tiers 1 to 3 | 58.6% | Not measured | Only Mistral Large 4 measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only Mistral Large 4 measured |
| ProofBench | 10.0% | 70.0% | MiMo-V2.6-Pro |
| LMArena Text: math | 1469 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1462 | 1511 | MiMo-V2.6-Pro |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Mistral Large 4 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.7% | 45.0% | MiMo-V2.6-Pro |
| SimpleQA Verified | 20.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: science | 1448 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1433 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1425 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1439 | 1468 | MiMo-V2.6-Pro |
| Neither model has a result on the other 12 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | Mistral Large 4 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1257 | 1308 | MiMo-V2.6-Pro |
| Design Arena: UI components | 1272 | 1340 | MiMo-V2.6-Pro |
| Design Arena: game dev | 1225 | 1314 | MiMo-V2.6-Pro |
| Design Arena: data viz | 1275 | 1336 | MiMo-V2.6-Pro |
| Design Arena: 3D | 1252 | 1330 | MiMo-V2.6-Pro |
| Design Arena: all code categories | 1259 | 1317 | MiMo-V2.6-Pro |
| Design Arena: SVG | 1232 | Not measured | Only Mistral Large 4 measured |
| Design Arena: ASCII art | 1202 | Not measured | Only Mistral Large 4 measured |
| LiveBench design | 65.6% | 78.5% | MiMo-V2.6-Pro |
GeneralLike-for-likePublic boards, shown as published, kept out of the index413
| Benchmark | Mistral Large 4 | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 57.8% | Only MiMo-V2.6-Pro measured |
| LiveBench data analysis | 76.5% | 72.3% | Mistral Large 4 |
| Public Benefits Bench (Vals AI) | Not measured | 68.9% | Only MiMo-V2.6-Pro measured |
| SAGE (Vals AI) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| MedScribe (Vals AI) | 80.4% | 88.3% | MiMo-V2.6-Pro |
| Long context reasoning (AA-LCR) | 81.3% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 88.2% | Not measured | Only Mistral Large 4 measured |
| LMCA | 35.8% | Not measured | Only Mistral Large 4 measured |
| Surface Evolver Bench | 28.1% | Not measured | Only Mistral Large 4 measured |
| Furniture assembly | 20.8% | Not measured | Only Mistral Large 4 measured |
| LMArena Text | 1431 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1422 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1363 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1272 | 1263 | Mistral Large 4 |
| LMArena Text: English | 1433 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1422 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1492 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: Japanese | 1415 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: French | 1492 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Spanish | 1455 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Russian | 1417 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: multi-turn | 1435 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1428 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1386 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1378 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1283 | 1268 | Mistral Large 4 |
| LMArena Vision: reading text | 1284 | 1270 | Mistral Large 4 |
| Neither model has a result on the other 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | 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 Large 4 | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Mistral AI | Xiaomi |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2026 | September 21, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.36 | $0.435 |
| Output $/Mtok | $4.18 | $0.87 |
| Coding index | 56.4 | 65.4 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 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 56.4 for Mistral Large 4, though on 4 benchmarks against 5. Pick Mistral Large 4 for work measured by IOI (Vals AI) or ALE-Bench, where it leads.
Which is cheaper, Mistral Large 4 or MiMo-V2.6-Pro?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; MiMo-V2.6-Pro costs $0.435 and $0.87. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large 4 or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 1.05M.
How many benchmarks is the Mistral Large 4 vs MiMo-V2.6-Pro comparison based on?
61 benchmarks have a result for both models as of October 22, 2026. Mistral Large 4's coding index rests on 5 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.