Qwen3.8 27B vs MiMo-V2.6-Pro
Qwen3.8 27B leads MiMo-V2.6-Pro on coding, 74.2 to 65.4 on the Vibe Coding Index, and MiMo-V2.6-Pro costs 2.9x less per output token ($0.87 vs $2.55 per million). Updated October 22, 2026; 58 benchmarks have a result for both.
Qwen3.8 27B or MiMo-V2.6-Pro: which to pick
Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 65.4 for MiMo-V2.6-Pro.
Pick MiMo-V2.6-Pro for output tokens 2.9x cheaper ($0.87 vs $2.55 per million) and a larger context window (1.05M against 1M tokens).
- Shared results
- 58
- Qwen3.8 27B only
- 27
- MiMo-V2.6-Pro only
- 15
- 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
Qwen3.8 27B
Qwen3.8 27B scores 74.2 against 65.4.
4 benchmarks behind each score
Intelligence
AA Intelligence Index
MiMo-V2.6-Pro
MiMo-V2.6-Pro leads, 46.3 against 33.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.8 27B has a AA Agentic Index result, 45.8.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.8 27B has a GPQA Diamond result, 88.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.8 27B has a MMLU Pro result, 84.3%.
Directional only
Web design
Design Arena: websites
No call
Only MiMo-V2.6-Pro has a Design Arena: websites result, 1308.
Directional only
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 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiMo-V2.6-Pro
Qwen3.8 27B $0.0017, MiMo-V2.6-Pro $0.0009 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.8 27B has the number, $1.26.
Directional only
At a glance
- Coding index
- Qwen3.8 27B 74.2 from 4 benchmarks, MiMo-V2.6-Pro 65.4 from 4 benchmarks.
- Widest category
- Math, 23.5 points apart on average over 3 shared benchmarks.
- Widest single gap
- LiveBench browser: Qwen3.8 27B 32.0% against MiMo-V2.6-Pro 88.0%, 56.0 points apart on a 0 to 100 scale.
- Output price
- Qwen3.8 27B $2.55 against MiMo-V2.6-Pro $0.87 per million output tokens, 2.9x apart.
- Context window
- Qwen3.8 27B takes 1M 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 | Qwen3.8 27B | Bars | MiMo-V2.6-Pro | Ties |
|---|---|---|---|---|
| Coding | 1 | 13 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 9 | ||
| Reasoning | 3 | 4 | ||
| Math | 0 | 3 | ||
| Knowledge | 0 | 5 | ||
| Web design | 0 | 1 | ||
| General | 4 | 14 | ||
| All shared boards | 8 | 50 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index113
| Benchmark | Qwen3.8 27B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| LiveBench coding | 86.8% | 81.5% | Qwen3.8 27B |
| LMArena WebDev | 1593 | 1625 | MiMo-V2.6-Pro |
| AA Coding Index | 68.1 | Not measured | Only Qwen3.8 27B measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only Qwen3.8 27B measured |
| SWE-bench Verified (Vals AI) | 86.0% | Not measured | Only Qwen3.8 27B measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 31.3% | Only MiMo-V2.6-Pro measured |
| Vibe Code Bench (Vals AI) | 64.8% | 85.2% | MiMo-V2.6-Pro |
| Code migration (Vals AI) | 14.2% | 43.0% | MiMo-V2.6-Pro |
| ProgramBench (Vals AI) | 0.0% | 0.5% | MiMo-V2.6-Pro |
| IOI (Vals AI) | 39.1% | 39.3% | MiMo-V2.6-Pro |
| Terminal-Bench 2.1 (Vals AI) | 58.4% | 67.8% | MiMo-V2.6-Pro |
| SWE-bench Multimodal (Vals AI) | Not measured | 41.3% | Only MiMo-V2.6-Pro measured |
| SkillsBench (Vals AI) | 38.1% | Not measured | Only Qwen3.8 27B measured |
| CyberBench (Vals AI) | 67.8% | 72.9% | MiMo-V2.6-Pro |
| SciCode | 46.6% | 60.9% | MiMo-V2.6-Pro |
| ALE-Bench | Not measured | 1158.1 | Only MiMo-V2.6-Pro measured |
| LMArena Text: coding | 1483 | 1533 | MiMo-V2.6-Pro |
| LMArena Text: software and IT | 1478 | 1528 | MiMo-V2.6-Pro |
| LMArena WebDev: React | 1602 | 1639 | MiMo-V2.6-Pro |
| LMArena WebDev: HTML | 1570 | 1616 | MiMo-V2.6-Pro |
| LMArena WebDev: from an image | 1577 | 1598 | MiMo-V2.6-Pro |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.8 27B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 33.7 | 46.3 | MiMo-V2.6-Pro |
| Epoch Capabilities Index | 151.7 | Not measured | Only Qwen3.8 27B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index09
| Benchmark | Qwen3.8 27B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 45.8 | Not measured | Only Qwen3.8 27B measured |
| Design Arena: agents building web apps | Not measured | 1290 | Only MiMo-V2.6-Pro measured |
| LiveBench research | 59.4% | 76.7% | MiMo-V2.6-Pro |
| LiveBench browser | 32.0% | 88.0% | MiMo-V2.6-Pro |
| LiveBench long agentic | 27.9% | 47.5% | MiMo-V2.6-Pro |
| SREBench (Vals AI) | Not measured | 3.0% | Only MiMo-V2.6-Pro measured |
| Finance Agent (Vals AI) | 48.5% | 57.3% | MiMo-V2.6-Pro |
| Tax Agent Bench (Vals AI) | 30.9% | 32.4% | MiMo-V2.6-Pro |
| Legal Research Bench (Vals AI) | 36.1% | 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) | 59.7% | 62.9% | MiMo-V2.6-Pro |
| Terminal-Bench-Science (Vals AI) | 0.0% | 2.9% | MiMo-V2.6-Pro |
| APEX-Agents | 47.5% | 54.4% | MiMo-V2.6-Pro |
| Neither model has a result on the other 28 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index34
| Benchmark | Qwen3.8 27B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 88.9% | Not measured | Only Qwen3.8 27B measured |
| LiveBench reasoning | 80.0% | 79.6% | Qwen3.8 27B |
| MysteryMechanism (Vals AI) | Not measured | 15.3% | Only MiMo-V2.6-Pro measured |
| MMMU Pro (Vals AI) | 83.9% | Not measured | Only Qwen3.8 27B measured |
| GPQA Diamond (Artificial Analysis run) | 90.5% | Not measured | Only Qwen3.8 27B measured |
| Humanity's Last Exam (Artificial Analysis run) | 33.9% | 49.4% | MiMo-V2.6-Pro |
| ARC-AGI | 87.5% | Not measured | Only Qwen3.8 27B measured |
| ARC-AGI-2 | 42.4% | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: hard prompts | 1459 | 1511 | MiMo-V2.6-Pro |
| LMArena Text: expert | 1479 | 1541 | MiMo-V2.6-Pro |
| LMArena Text: hard prompts in English | 1461 | 1520 | MiMo-V2.6-Pro |
| LMArena Vision: diagrams | 1285 | 1281 | Qwen3.8 27B |
| LMArena Vision: homework | 1295 | 1264 | Qwen3.8 27B |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Qwen3.8 27B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| ProofBench | 16.0% | 70.0% | MiMo-V2.6-Pro |
| LMArena Text: math | 1455 | 1500 | MiMo-V2.6-Pro |
| LMArena Text: mathematical work | 1458 | 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 | Qwen3.8 27B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| MMLU Pro | 84.3% | Not measured | Only Qwen3.8 27B measured |
| LegalBench (Vals AI) | 82.4% | Not measured | Only Qwen3.8 27B measured |
| TaxEval (Vals AI) | 70.8% | Not measured | Only Qwen3.8 27B measured |
| MortgageTax (Vals AI) | 64.9% | Not measured | Only Qwen3.8 27B measured |
| MedCode (Vals AI) | 28.7% | 45.0% | MiMo-V2.6-Pro |
| LMArena Text: science | 1467 | 1506 | MiMo-V2.6-Pro |
| LMArena Text: medicine and healthcare | 1437 | 1497 | MiMo-V2.6-Pro |
| LMArena Text: legal and government | 1447 | 1485 | MiMo-V2.6-Pro |
| LMArena Text: business and finance | 1438 | 1468 | MiMo-V2.6-Pro |
| Neither model has a result on the other 9 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.8 27B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1308 | Only MiMo-V2.6-Pro measured |
| Design Arena: UI components | Not measured | 1340 | Only MiMo-V2.6-Pro measured |
| Design Arena: game dev | Not measured | 1314 | Only MiMo-V2.6-Pro measured |
| Design Arena: data viz | Not measured | 1336 | Only MiMo-V2.6-Pro measured |
| Design Arena: 3D | Not measured | 1330 | Only MiMo-V2.6-Pro measured |
| Design Arena: all code categories | Not measured | 1317 | Only MiMo-V2.6-Pro measured |
| LiveBench design | 75.9% | 78.5% | MiMo-V2.6-Pro |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index414
| Benchmark | Qwen3.8 27B | MiMo-V2.6-Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 57.8% | Only MiMo-V2.6-Pro measured |
| LiveBench data analysis | 76.6% | 72.3% | Qwen3.8 27B |
| Public Benefits Bench (Vals AI) | Not measured | 68.9% | Only MiMo-V2.6-Pro measured |
| SAGE (Vals AI) | 52.4% | 45.0% | Qwen3.8 27B |
| MedScribe (Vals AI) | 83.8% | 88.3% | MiMo-V2.6-Pro |
| Long context reasoning (AA-LCR) | 82.0% | 86.3% | MiMo-V2.6-Pro |
| DTBench | 88.0% | Not measured | Only Qwen3.8 27B measured |
| LMCA | 41.4% | Not measured | Only Qwen3.8 27B measured |
| Surface Evolver Bench | 45.0% | Not measured | Only Qwen3.8 27B measured |
| LMArena Text | 1440 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: instruction following | 1436 | 1491 | MiMo-V2.6-Pro |
| LMArena Text: creative writing | 1383 | 1466 | MiMo-V2.6-Pro |
| LMArena Vision | 1269 | 1263 | Qwen3.8 27B |
| LMArena Text: English | 1448 | 1504 | MiMo-V2.6-Pro |
| LMArena Text: non-English | 1428 | 1474 | MiMo-V2.6-Pro |
| LMArena Text: Chinese | 1501 | 1529 | MiMo-V2.6-Pro |
| LMArena Text: German | 1443 | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: Japanese | 1387 | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: Korean | 1384 | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: French | 1465 | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: Spanish | 1449 | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: Russian | 1415 | 1479 | MiMo-V2.6-Pro |
| LMArena Text: Polish | 1439 | Not measured | Only Qwen3.8 27B measured |
| LMArena Text: multi-turn | 1440 | 1466 | MiMo-V2.6-Pro |
| LMArena Text: longer queries | 1448 | 1501 | MiMo-V2.6-Pro |
| LMArena Text: writing and language | 1405 | 1470 | MiMo-V2.6-Pro |
| LMArena Text: entertainment and media | 1393 | 1465 | MiMo-V2.6-Pro |
| LMArena Vision: English | 1267 | 1268 | MiMo-V2.6-Pro |
| LMArena Vision: Chinese | 1326 | Not measured | Only Qwen3.8 27B measured |
| LMArena Vision: reading text | 1281 | 1270 | Qwen3.8 27B |
| LMArena Vision: humor | 1235 | Not measured | Only Qwen3.8 27B measured |
| LMArena Vision: creative writing | 1237 | Not measured | Only Qwen3.8 27B 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 | Qwen3.8 27B | 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 | Qwen3.8 27B | Xiaomi MiMo-V2.6-Pro |
|---|---|---|
| Maker | Qwen | Xiaomi |
| Weights | Open weights | Open weights |
| Released | August 14, 2026 | September 21, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $0.425 | $0.435 |
| Output $/Mtok | $2.55 | $0.87 |
| Coding index | 74.2 | 65.4 |
| Independent measurements behind it | 4 | 4 |
| Cost per solved task | $1.26 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.8 27B better than MiMo-V2.6-Pro for coding?
Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 65.4 for MiMo-V2.6-Pro. Pick MiMo-V2.6-Pro for output tokens 2.9x cheaper ($0.87 vs $2.55 per million) and a larger context window (1.05M against 1M tokens).
Which is cheaper, Qwen3.8 27B or MiMo-V2.6-Pro?
Qwen3.8 27B costs $0.425 per million input tokens and $2.55 per million output tokens; MiMo-V2.6-Pro costs $0.435 and $0.87. Cost per solved task is known for Qwen3.8 27B only.
Which has the bigger context window, Qwen3.8 27B or MiMo-V2.6-Pro?
MiMo-V2.6-Pro, with 1.05M tokens against 1M.
How many benchmarks is the Qwen3.8 27B vs MiMo-V2.6-Pro comparison based on?
58 benchmarks have a result for both models as of October 22, 2026. Qwen3.8 27B's coding index rests on 4 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.