Qwen3.5 397B A17B vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads Qwen3.5 397B A17B on the Artificial Analysis Intelligence Index, 46.3 to 21.4, and MiMo-V2.6-Pro costs 2.7x less per output token ($0.87 vs $2.34 per million). Updated October 22, 2026; 42 benchmarks have a result for both.
Qwen3.5 397B A17B or MiMo-V2.6-Pro: which to pick
Only MiMo-V2.6-Pro has a coding score, 65.4 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding.
Pick Qwen3.5 397B A17B for work measured by LMArena Vision: homework or LMArena Vision: English, where it leads.
- Shared results
- 42
- Qwen3.5 397B A17B only
- 24
- MiMo-V2.6-Pro only
- 31
- 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
No call
Only MiMo-V2.6-Pro has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 46.3 against 21.4.
Same board, both measured
Web design
Design Arena: websites
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 1307 against 1190.
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
Qwen3.5 397B A17B $0.0016, MiMo-V2.6-Pro $0.0009 per turn.
List prices
At a glance
- Coding index
- Qwen3.5 397B A17B not benchmarked, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Agentic work, 29.5 points apart on average over 1 shared benchmark.
- Widest single gap
- LMArena WebDev: React: Qwen3.5 397B A17B 1388 against MiMo-V2.6-Pro 1639, 35.4 points apart on a 0 to 100 scale.
- Output price
- Qwen3.5 397B A17B $2.34 against MiMo-V2.6-Pro $0.87 per million output tokens, 2.7x apart.
- Context window
- Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| Web design | 0 | 6 | ||
| General | 2 | 13 | ||
| All shared boards | 3 | 39 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
| Benchmark | Qwen3.5 397B A17B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 81.5% | Only MiMo-V2.6-Pro measured |
| LMArena WebDev | 1400 | 1625 | MiMo-V2.6-Pro |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.3% | Only MiMo-V2.6-Pro measured |
| Vibe Code Bench (Vals AI) | Not measured | 85.2% | Only MiMo-V2.6-Pro measured |
| Code migration (Vals AI) | Not measured | 43.0% | Only MiMo-V2.6-Pro measured |
| 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) | Not measured | 67.8% | Only MiMo-V2.6-Pro measured |
| 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 | 44.8% | 60.9% | MiMo-V2.6-Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 40.9% | Not measured | Only Qwen3.5 397B A17B measured |
| ALE-Bench | 621.9 | 1158.1 | MiMo-V2.6-Pro |
| LMArena Text: coding | 1464 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1463 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | 1388 | 1639 | MiMo-V2.6-Pro |
| LMArena WebDev: HTML | 1410 | 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 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5 397B A17B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 21.4 | 46.3 | MiMo-V2.6-Pro |
| Epoch Capabilities Index | 146.8 | Not measured | Only Qwen3.5 397B A17B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5 397B A17B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| 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) | Not measured | 57.3% | Only MiMo-V2.6-Pro measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.4% | Only MiMo-V2.6-Pro measured |
| Legal Research Bench (Vals AI) | Not measured | 47.1% | Only MiMo-V2.6-Pro measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 13.8% | Only MiMo-V2.6-Pro measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 62.9% | Only MiMo-V2.6-Pro measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 2.9% | Only MiMo-V2.6-Pro measured |
| τ²-Bench Telecom | 95.6% | Not measured | Only Qwen3.5 397B A17B measured |
| APEX-Agents | 24.9% | 54.4% | MiMo-V2.6-Pro |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Qwen3.5 397B A17B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| 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) | 89.3% | Not measured | Only Qwen3.5 397B A17B measured |
| Humanity's Last Exam (Artificial Analysis run) | 29.0% | 49.4% | MiMo-V2.6-Pro |
| GPQA Diamond (Epoch AI run) | 86.4% | Not measured | Only Qwen3.5 397B A17B measured |
| Mystery game puzzles | 18.0% | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | 1448 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1462 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1450 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1277 | 1281 | MiMo-V2.6-Pro |
| LMArena Vision: homework | 1292 | 1264 | Qwen3.5 397B A17B |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3.5 397B A17B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 88.9% | Not measured | Only Qwen3.5 397B A17B measured |
| FrontierMath, tiers 1 to 3 | 31.2% | Not measured | Only Qwen3.5 397B A17B measured |
| ProofBench | Not measured | 70.0% | Only MiMo-V2.6-Pro measured |
| LMArena Text: math | 1453 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1454 | 1511 | MiMo-V2.6-Pro |
| MathArena | 19.2% | Not measured | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen3.5 397B A17B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| LMArena Text: science | 1457 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1455 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1441 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1435 | 1468 | MiMo-V2.6-Pro |
| Neither model has a result on the other 15 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Qwen3.5 397B A17B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1190 | 1307 | MiMo-V2.6-Pro |
| Design Arena: UI components | 1161 | 1337 | MiMo-V2.6-Pro |
| Design Arena: game dev | 1140 | 1313 | MiMo-V2.6-Pro |
| Design Arena: data viz | 1175 | 1337 | MiMo-V2.6-Pro |
| Design Arena: 3D | 1160 | 1329 | MiMo-V2.6-Pro |
| Design Arena: all code categories | 1179 | 1316 | MiMo-V2.6-Pro |
| Design Arena: SVG | 1139 | Not measured | Only Qwen3.5 397B A17B measured |
| LiveBench design | Not measured | 78.5% | Only MiMo-V2.6-Pro measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index213
| Benchmark | Qwen3.5 397B A17B | 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) | Not measured | 45.0% | Only MiMo-V2.6-Pro measured |
| MedScribe (Vals AI) | Not measured | 88.3% | Only MiMo-V2.6-Pro measured |
| IFBench | 78.8% | Not measured | Only Qwen3.5 397B A17B measured |
| Long context reasoning (AA-LCR) | 77.3% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 87.5% | Not measured | Only Qwen3.5 397B A17B measured |
| LMCA | 37.9% | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text | 1437 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1424 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1402 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1262 | 1263 | MiMo-V2.6-Pro |
| LMArena Text: English | 1443 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1430 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1498 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: German | 1445 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: Japanese | 1429 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: Korean | 1384 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: French | 1462 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: Spanish | 1441 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: Russian | 1430 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: Polish | 1447 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Text: multi-turn | 1446 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1441 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1415 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1399 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1268 | 1268 | Qwen3.5 397B A17B |
| LMArena Vision: Chinese | 1314 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | 1271 | 1270 | Qwen3.5 397B A17B |
| LMArena Vision: humor | 1262 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | 1230 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | 1265 | Not measured | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | 1260 | Not measured | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5 397B A17B | 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 | Qwen3.5 397B A17B | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Qwen | Xiaomi |
| Weights | Open weights | Open weights |
| Released | February 16, 2026 | September 21, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.39 | $0.435 |
| Output $/Mtok | $2.34 | $0.87 |
| Coding index | Not benchmarked | 65.4 |
| Independent measurements behind it | 1 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.5 397B A17B better than MiMo-V2.6-Pro for coding?
Only MiMo-V2.6-Pro has a coding score, 65.4 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding. Pick Qwen3.5 397B A17B for work measured by LMArena Vision: homework or LMArena Vision: English, where it leads.
Which is cheaper, Qwen3.5 397B A17B or MiMo-V2.6-Pro?
Qwen3.5 397B A17B costs $0.39 per million input tokens and $2.34 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, Qwen3.5 397B A17B or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 262K.
How many benchmarks is the Qwen3.5 397B A17B vs MiMo-V2.6-Pro comparison based on?
42 benchmarks have a result for both models as of October 22, 2026. Qwen3.5 397B A17B's coding index rests on 1 independent benchmark and MiMo-V2.6-Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.