Qwen3.5-35B-A3B vs MiMo-V2.5-Pro
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-V2.5-Pro for coding: it scores 40.0 on the Vibe Coding Index against 7.7 for Qwen3.5-35B-A3B.
Qwen3.5-35B-A3B is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 41
- Qwen3.5-35B-A3B only
- 4
- MiMo-V2.5-Pro only
- 29
- Like-for-like categories
- 7 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-V2.5-Pro
MiMo-V2.5-Pro scores 40.0 against 7.7.
One benchmark behind each score
Intelligence
AA Intelligence Index
MiMo-V2.5-Pro
MiMo-V2.5-Pro leads, 26.0 against 19.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiMo-V2.5-Pro has a AA Agentic Index result, 21.3.
Directional only
Reasoning
GPQA Diamond
No call
Only MiMo-V2.5-Pro has a GPQA Diamond result, 82.6%.
Directional only
Knowledge
MMLU Pro
No call
Only MiMo-V2.5-Pro has a MMLU Pro result, 84.6%.
Directional only
Web design
Design Arena: websites
No call
Only MiMo-V2.5-Pro has a Design Arena: websites result, 1267.
Directional only
Long documents
Listed context window
MiMo-V2.5-Pro
MiMo-V2.5-Pro takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.5-Pro
Qwen3.5-35B-A3B $0.0006, MiMo-V2.5-Pro $0.0006 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiMo-V2.5-Pro has the number, $0.03.
Directional only
At a glance
- Coding index
- Qwen3.5-35B-A3B 7.7 from 1 benchmark, MiMo-V2.5-Pro 40.0 from 1 benchmark.
- Widest category
- Coding, 23.9 points apart on average over 7 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Qwen3.5-35B-A3B 1238 against MiMo-V2.5-Pro 1469, 38.6 points apart on a 0 to 100 scale.
- Output price
- Qwen3.5-35B-A3B $1.00 against MiMo-V2.5-Pro $0.609 per million output tokens, 1.6x apart.
- Context window
- Qwen3.5-35B-A3B takes 262K tokens, MiMo-V2.5-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 | Qwen3.5-35B-A3B | Bars | MiMo-V2.5-Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 7 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 21 | ||
| All shared boards | 0 | 41 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index07
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| LMArena WebDev | 1254 | 1480 | MiMo-V2.5-Pro |
| AA Coding Index | Not measured | 60.2 | Only MiMo-V2.5-Pro measured |
| LiveCodeBench (Vals AI) | Not measured | 81.3% | Only MiMo-V2.5-Pro measured |
| SWE-bench Verified (Vals AI) | Not measured | 74.0% | Only MiMo-V2.5-Pro measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 0.5% | Only MiMo-V2.5-Pro measured |
| Vibe Code Bench (Vals AI) | Not measured | 34.1% | Only MiMo-V2.5-Pro measured |
| Code migration (Vals AI) | Not measured | 21.6% | Only MiMo-V2.5-Pro measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 57.3% | Only MiMo-V2.5-Pro measured |
| SciCode | Not measured | 50.6% | Only MiMo-V2.5-Pro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 43.2% | MiMo-V2.5-Pro |
| ALE-Bench | 221.8 | 899.8 | MiMo-V2.5-Pro |
| LMArena Text: coding | 1410 | 1501 | MiMo-V2.5-Pro |
| LMArena Text: software and IT | 1415 | 1495 | MiMo-V2.5-Pro |
| LMArena WebDev: React | 1238 | 1469 | MiMo-V2.5-Pro |
| LMArena WebDev: HTML | 1301 | 1473 | MiMo-V2.5-Pro |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 19.3 | 26.0 | MiMo-V2.5-Pro |
| Epoch Capabilities Index | 142.5 | Not measured | Only Qwen3.5-35B-A3B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 21.3 | Only MiMo-V2.5-Pro measured |
| Finance Agent (Vals AI) | Not measured | 41.5% | Only MiMo-V2.5-Pro measured |
| Tax Agent Bench (Vals AI) | Not measured | 11.5% | Only MiMo-V2.5-Pro measured |
| Legal Research Bench (Vals AI) | Not measured | 15.9% | Only MiMo-V2.5-Pro measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 55.2% | Only MiMo-V2.5-Pro measured |
| τ²-Bench Telecom | 89.2% | 94.2% | MiMo-V2.5-Pro |
| Vending-Bench 2 | $463 | Not measured | Only Qwen3.5-35B-A3B measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 82.6% | Only MiMo-V2.5-Pro measured |
| GPQA Diamond (Artificial Analysis run) | 84.5% | 86.6% | MiMo-V2.5-Pro |
| Humanity's Last Exam (Artificial Analysis run) | 21.0% | 35.7% | MiMo-V2.5-Pro |
| GPQA Diamond (Epoch AI run) | 83.5% | Not measured | Only Qwen3.5-35B-A3B measured |
| LMArena Text: hard prompts | 1400 | 1486 | MiMo-V2.5-Pro |
| LMArena Text: expert | 1408 | 1501 | MiMo-V2.5-Pro |
| LMArena Text: hard prompts in English | 1411 | 1494 | MiMo-V2.5-Pro |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 70.0% | Not measured | Only Qwen3.5-35B-A3B measured |
| ProofBench | Not measured | 22.0% | Only MiMo-V2.5-Pro measured |
| LMArena Text: math | 1404 | 1481 | MiMo-V2.5-Pro |
| LMArena Text: mathematical work | 1410 | 1491 | MiMo-V2.5-Pro |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.6% | Only MiMo-V2.5-Pro measured |
| LegalBench (Vals AI) | Not measured | 77.1% | Only MiMo-V2.5-Pro measured |
| CorpFin (Vals AI) | Not measured | 61.4% | Only MiMo-V2.5-Pro measured |
| TaxEval (Vals AI) | Not measured | 73.8% | Only MiMo-V2.5-Pro measured |
| MedCode (Vals AI) | Not measured | 32.5% | Only MiMo-V2.5-Pro measured |
| LMArena Text: science | 1413 | 1482 | MiMo-V2.5-Pro |
| LMArena Text: medicine and healthcare | 1421 | 1473 | MiMo-V2.5-Pro |
| LMArena Text: legal and government | 1399 | 1474 | MiMo-V2.5-Pro |
| LMArena Text: business and finance | 1394 | 1466 | MiMo-V2.5-Pro |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1267 | Only MiMo-V2.5-Pro measured |
| Design Arena: UI components | Not measured | 1248 | Only MiMo-V2.5-Pro measured |
| Design Arena: game dev | Not measured | 1261 | Only MiMo-V2.5-Pro measured |
| Design Arena: data viz | Not measured | 1257 | Only MiMo-V2.5-Pro measured |
| Design Arena: 3D | Not measured | 1244 | Only MiMo-V2.5-Pro measured |
| Design Arena: all code categories | Not measured | 1266 | Only MiMo-V2.5-Pro measured |
| Design Arena: SVG | Not measured | 1181 | Only MiMo-V2.5-Pro measured |
| Design Arena: ASCII art | Not measured | 1157 | Only MiMo-V2.5-Pro measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-Pro | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | Not measured | 83.7% | Only MiMo-V2.5-Pro measured |
| IFBench | 72.5% | 79.9% | MiMo-V2.5-Pro |
| Long context reasoning (AA-LCR) | 72.0% | 79.7% | MiMo-V2.5-Pro |
| DTBench | 80.0% | 84.5% | MiMo-V2.5-Pro |
| LMCA | 29.5% | 29.5% | MiMo-V2.5-Pro |
| LMArena Text | 1395 | 1464 | MiMo-V2.5-Pro |
| LMArena Text: instruction following | 1379 | 1475 | MiMo-V2.5-Pro |
| LMArena Text: creative writing | 1347 | 1438 | MiMo-V2.5-Pro |
| LMArena Text: English | 1407 | 1477 | MiMo-V2.5-Pro |
| LMArena Text: non-English | 1378 | 1448 | MiMo-V2.5-Pro |
| LMArena Text: Chinese | 1457 | 1507 | MiMo-V2.5-Pro |
| LMArena Text: German | 1367 | 1459 | MiMo-V2.5-Pro |
| LMArena Text: Japanese | 1326 | 1410 | MiMo-V2.5-Pro |
| LMArena Text: Korean | 1355 | 1435 | MiMo-V2.5-Pro |
| LMArena Text: French | 1412 | 1487 | MiMo-V2.5-Pro |
| LMArena Text: Spanish | 1390 | 1469 | MiMo-V2.5-Pro |
| LMArena Text: Russian | 1376 | 1449 | MiMo-V2.5-Pro |
| LMArena Text: Polish | 1385 | 1464 | MiMo-V2.5-Pro |
| LMArena Text: multi-turn | 1390 | 1476 | MiMo-V2.5-Pro |
| LMArena Text: longer queries | 1389 | 1481 | MiMo-V2.5-Pro |
| LMArena Text: writing and language | 1365 | 1451 | MiMo-V2.5-Pro |
| LMArena Text: entertainment and media | 1347 | 1438 | MiMo-V2.5-Pro |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5-35B-A3B | MiMo-V2.5-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-V2.5-Pro costs less
Repository review
50K input + 3K output tokens
Qwen3.5-35B-A3B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-35B-A3B 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 | Qwen3.5-35B-A3B | Xiaomi MiMo-V2.5-Pro |
|---|---|---|
| Maker | Qwen | Xiaomi |
| Weights | Open weights | Open weights |
| Released | February 25, 2026 | April 22, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.14 | $0.3045 |
| Output $/Mtok | $1.00 | $0.609 |
| Coding index | 7.7 | 40.0 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | $0.03 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.5-35B-A3B better than MiMo-V2.5-Pro for coding?
Pick MiMo-V2.5-Pro for coding: it scores 40.0 on the Vibe Coding Index against 7.7 for Qwen3.5-35B-A3B. Qwen3.5-35B-A3B is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, Qwen3.5-35B-A3B or MiMo-V2.5-Pro?
Qwen3.5-35B-A3B costs $0.14 per million input tokens and $1.00 per million output tokens; MiMo-V2.5-Pro costs $0.3045 and $0.609. Cost per solved task is known for MiMo-V2.5-Pro only.
Which has the bigger context window, Qwen3.5-35B-A3B or MiMo-V2.5-Pro?
MiMo-V2.5-Pro, with 1.05M tokens against 262K.
How many benchmarks is the Qwen3.5-35B-A3B vs MiMo-V2.5-Pro comparison based on?
41 benchmarks have a result for both models as of October 21, 2026. Qwen3.5-35B-A3B's coding index rests on 1 independent benchmark and MiMo-V2.5-Pro's on 1. Where only one model has a result, the page says so instead of naming a winner.