Qwen3.5-122B-A10B vs MiMo-V2.6-Flash
Updated October 21, 2026. 41 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick MiMo-V2.6-Flash for coding: it scores 61.9 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B.
Pick Qwen3.5-122B-A10B when what matters is Long context reasoning (AA-LCR) or LMArena Text: Japanese, where it leads.
- Shared results
- 41
- Qwen3.5-122B-A10B only
- 10
- MiMo-V2.6-Flash only
- 25
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
MiMo-V2.6-Flash
MiMo-V2.6-Flash scores 61.9 against 22.9.
One benchmark behind each score
Intelligence
AA Intelligence Index
MiMo-V2.6-Flash
MiMo-V2.6-Flash leads, 37.9 against 17.7.
Same board, both measured
General
Vals Index
No call
Only MiMo-V2.6-Flash has a Vals Index result, 54.8%.
Directional only
Long documents
Listed context window
MiMo-V2.6-Flash
MiMo-V2.6-Flash takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Flash
Qwen3.5-122B-A10B $0.0013, MiMo-V2.6-Flash $0.0003 per turn.
List prices
At a glance
- Coding index
- Qwen3.5-122B-A10B 22.9 from 1 benchmark, MiMo-V2.6-Flash 61.9 from 1 benchmark.
- Widest category
- Coding, 25.7 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena WebDev: HTML: Qwen3.5-122B-A10B 1351 against MiMo-V2.6-Flash 1641, 41.4 points apart on a 0 to 100 scale.
- Output price
- Qwen3.5-122B-A10B $2.08 against MiMo-V2.6-Flash $0.28 per million output tokens, 7.4x apart.
- Context window
- Qwen3.5-122B-A10B takes 262K tokens, MiMo-V2.6-Flash 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 | Qwen3.5-122B-A10B | Bars | MiMo-V2.6-Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 2 | 20 | ||
| All shared boards | 2 | 39 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index06
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| LMArena WebDev | 1361 | 1634 | MiMo-V2.6-Flash |
| AA Coding Index | 43.3 | Not measured | Only Qwen3.5-122B-A10B measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 24.2% | Only MiMo-V2.6-Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 79.0% | Only MiMo-V2.6-Flash measured |
| Code migration (Vals AI) | Not measured | 40.9% | Only MiMo-V2.6-Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.5% | Only MiMo-V2.6-Flash measured |
| IOI (Vals AI) | Not measured | 47.7% | Only MiMo-V2.6-Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 76.4% | Only MiMo-V2.6-Flash measured |
| CyberBench (Vals AI) | Not measured | 75.4% | Only MiMo-V2.6-Flash measured |
| SciCode | 39.7% | 51.3% | MiMo-V2.6-Flash |
| Terminal-Bench Hard (Artificial Analysis run) | 31.1% | Not measured | Only Qwen3.5-122B-A10B measured |
| ALE-Bench | Not measured | 1244.2 | Only MiMo-V2.6-Flash measured |
| LMArena Text: coding | 1436 | 1499 | MiMo-V2.6-Flash |
| LMArena Text: software and IT | 1436 | 1497 | MiMo-V2.6-Flash |
| LMArena WebDev: React | 1353 | 1648 | MiMo-V2.6-Flash |
| LMArena WebDev: HTML | 1351 | 1641 | MiMo-V2.6-Flash |
| LMArena WebDev: from an image | Not measured | 1596 | Only MiMo-V2.6-Flash measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 17.7 | 37.9 | MiMo-V2.6-Flash |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| SREBench (Vals AI) | Not measured | 4.2% | Only MiMo-V2.6-Flash measured |
| Finance Agent (Vals AI) | Not measured | 56.3% | Only MiMo-V2.6-Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 28.5% | Only MiMo-V2.6-Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 38.0% | Only MiMo-V2.6-Flash measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 13.3% | Only MiMo-V2.6-Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 65.5% | Only MiMo-V2.6-Flash measured |
| BioMysteryBench (Vals AI) | Not measured | 69.3% | Only MiMo-V2.6-Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 4.3% | Only MiMo-V2.6-Flash measured |
| Vals Science Index | Not measured | 31.7% | Only MiMo-V2.6-Flash measured |
| τ²-Bench Telecom | 93.6% | Not measured | Only Qwen3.5-122B-A10B measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | Not measured | 21.6% | Only MiMo-V2.6-Flash measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | Not measured | Only Qwen3.5-122B-A10B measured |
| Humanity's Last Exam (Artificial Analysis run) | 25.2% | 35.1% | MiMo-V2.6-Flash |
| Mystery game puzzles | 17.0% | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text: hard prompts | 1421 | 1475 | MiMo-V2.6-Flash |
| LMArena Text: expert | 1431 | 1496 | MiMo-V2.6-Flash |
| LMArena Text: hard prompts in English | 1431 | 1493 | MiMo-V2.6-Flash |
| LMArena Vision: diagrams | 1249 | 1276 | MiMo-V2.6-Flash |
| LMArena Vision: homework | 1261 | 1283 | MiMo-V2.6-Flash |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| ProofBench | Not measured | 63.0% | Only MiMo-V2.6-Flash measured |
| LMArena Text: math | 1431 | 1476 | MiMo-V2.6-Flash |
| LMArena Text: mathematical work | 1431 | 1478 | MiMo-V2.6-Flash |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 41.1% | Only MiMo-V2.6-Flash measured |
| LMArena Text: science | 1432 | 1462 | MiMo-V2.6-Flash |
| LMArena Text: medicine and healthcare | 1423 | 1439 | MiMo-V2.6-Flash |
| LMArena Text: legal and government | 1422 | 1441 | MiMo-V2.6-Flash |
| LMArena Text: business and finance | 1414 | 1454 | MiMo-V2.6-Flash |
| Neither model has a result on the other 12 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index220
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | Leader |
|---|---|---|---|
| Vals Index | Not measured | 54.8% | Only MiMo-V2.6-Flash measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.6% | Only MiMo-V2.6-Flash measured |
| SAGE (Vals AI) | Not measured | 43.5% | Only MiMo-V2.6-Flash measured |
| MedScribe (Vals AI) | Not measured | 85.3% | Only MiMo-V2.6-Flash measured |
| IFBench | 75.7% | Not measured | Only Qwen3.5-122B-A10B measured |
| Long context reasoning (AA-LCR) | 76.3% | 74.3% | Qwen3.5-122B-A10B |
| DTBench | 84.3% | Not measured | Only Qwen3.5-122B-A10B measured |
| LMCA | 32.2% | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Text | 1417 | 1453 | MiMo-V2.6-Flash |
| LMArena Text: instruction following | 1399 | 1452 | MiMo-V2.6-Flash |
| LMArena Text: creative writing | 1368 | 1403 | MiMo-V2.6-Flash |
| LMArena Vision | 1244 | 1256 | MiMo-V2.6-Flash |
| LMArena Text: English | 1428 | 1476 | MiMo-V2.6-Flash |
| LMArena Text: non-English | 1401 | 1431 | MiMo-V2.6-Flash |
| LMArena Text: Chinese | 1463 | 1509 | MiMo-V2.6-Flash |
| LMArena Text: German | 1425 | 1458 | MiMo-V2.6-Flash |
| LMArena Text: Japanese | 1367 | 1359 | Qwen3.5-122B-A10B |
| LMArena Text: Korean | 1353 | 1425 | MiMo-V2.6-Flash |
| LMArena Text: French | 1443 | 1480 | MiMo-V2.6-Flash |
| LMArena Text: Spanish | 1425 | 1453 | MiMo-V2.6-Flash |
| LMArena Text: Russian | 1400 | 1409 | MiMo-V2.6-Flash |
| LMArena Text: Polish | 1398 | 1455 | MiMo-V2.6-Flash |
| LMArena Text: multi-turn | 1416 | 1447 | MiMo-V2.6-Flash |
| LMArena Text: longer queries | 1410 | 1459 | MiMo-V2.6-Flash |
| LMArena Text: writing and language | 1387 | 1424 | MiMo-V2.6-Flash |
| LMArena Text: entertainment and media | 1366 | 1415 | MiMo-V2.6-Flash |
| LMArena Vision: English | 1249 | 1269 | MiMo-V2.6-Flash |
| LMArena Vision: Chinese | 1301 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: reading text | 1251 | 1270 | MiMo-V2.6-Flash |
| LMArena Vision: humor | 1243 | Not measured | Only Qwen3.5-122B-A10B measured |
| LMArena Vision: creative writing | 1220 | 1231 | MiMo-V2.6-Flash |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5-122B-A10B | MiMo-V2.6-Flash | 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-Flash costs less
Repository review
50K input + 3K output tokens
MiMo-V2.6-Flash costs less
Agent loop
200K input + 10K output tokens
MiMo-V2.6-Flash 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 | Qwen3.5-122B-A10B | Xiaomi MiMo-V2.6-Flash |
|---|---|---|
| Maker | Qwen | Xiaomi |
| Weights | Open weights | Open weights |
| Released | February 25, 2026 | September 21, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.26 | $0.14 |
| Output $/Mtok | $2.08 | $0.28 |
| Coding index | 22.9 | 61.9 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.5-122B-A10B better than MiMo-V2.6-Flash for coding?
Pick MiMo-V2.6-Flash for coding: it scores 61.9 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B. Pick Qwen3.5-122B-A10B when what matters is Long context reasoning (AA-LCR) or LMArena Text: Japanese, where it leads.
Which is cheaper, Qwen3.5-122B-A10B or MiMo-V2.6-Flash?
Qwen3.5-122B-A10B costs $0.26 per million input tokens and $2.08 per million output tokens; MiMo-V2.6-Flash costs $0.14 and $0.28. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen3.5-122B-A10B or MiMo-V2.6-Flash?
MiMo-V2.6-Flash, with 1.05M tokens against 262K.
How many benchmarks is the Qwen3.5-122B-A10B vs MiMo-V2.6-Flash comparison based on?
41 benchmarks have a result for both models as of October 21, 2026. Qwen3.5-122B-A10B's coding index rests on 1 independent benchmark and MiMo-V2.6-Flash's on 1. Where only one model has a result, the page says so instead of naming a winner.