MiniMax M3.1 Flash vs Qwen3.8 27B
Qwen3.8 27B leads MiniMax M3.1 Flash on coding, 74.2 to 59.0 on the Vibe Coding Index, and MiniMax M3.1 Flash costs 4.3x less per output token ($0.60 vs $2.55 per million). Updated October 22, 2026; 17 benchmarks have a result for both.
MiniMax M3.1 Flash or Qwen3.8 27B: which to pick
Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 59.0 for MiniMax M3.1 Flash.
Pick MiniMax M3.1 Flash for output tokens 4.3x cheaper ($0.60 vs $2.55 per million) and work measured by Vibe Code Bench (Vals AI) or SciCode, where it leads.
- Shared results
- 17
- MiniMax M3.1 Flash only
- 3
- Qwen3.8 27B only
- 68
- Like-for-like categories
- 6 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 59.0.
4 benchmarks behind each score
Intelligence
AA Intelligence Index
MiniMax M3.1 Flash
MiniMax M3.1 Flash leads, 42.7 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
General
Vals Index
No call
Only MiniMax M3.1 Flash has a Vals Index result, 53.8%.
Directional only
Long documents
Listed context window
No call
Both take 1M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M3.1 Flash
MiniMax M3.1 Flash $0.0004, Qwen3.8 27B $0.0017 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
- MiniMax M3.1 Flash 59.0 from 4 benchmarks, Qwen3.8 27B 74.2 from 4 benchmarks.
- Widest category
- Agentic work, 16.7 points apart on average over 5 shared benchmarks.
- Widest single gap
- LiveBench browser: MiniMax M3.1 Flash 92.0% against Qwen3.8 27B 32.0%, 60.0 points apart on a 0 to 100 scale.
- Output price
- MiniMax M3.1 Flash $0.60 against Qwen3.8 27B $2.55 per million output tokens, 4.3x apart.
- Context window
- Both take 1M tokens.
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 | MiniMax M3.1 Flash | Bars | Qwen3.8 27B | Ties |
|---|---|---|---|---|
| Coding | 3 | 3 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 4 | 1 | ||
| Reasoning | 2 | 0 | ||
| Web design | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 10 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index33
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | Leader |
|---|---|---|---|
| LiveBench coding | 83.9% | 86.8% | Qwen3.8 27B |
| LMArena WebDev | 1587 | 1593 | Qwen3.8 27B |
| AA Coding Index | Not measured | 68.1 | Only Qwen3.8 27B measured |
| LiveCodeBench (Vals AI) | Not measured | 84.0% | Only Qwen3.8 27B measured |
| SWE-bench Verified (Vals AI) | Not measured | 86.0% | Only Qwen3.8 27B measured |
| Terminal-Bench 4 (Vals AI) | 25.3% | Not measured | Only MiniMax M3.1 Flash measured |
| Vibe Code Bench (Vals AI) | 73.9% | 64.8% | MiniMax M3.1 Flash |
| Code migration (Vals AI) | Not measured | 14.2% | Only Qwen3.8 27B measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.8 27B measured |
| IOI (Vals AI) | Not measured | 39.1% | Only Qwen3.8 27B measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 58.4% | Only Qwen3.8 27B measured |
| SkillsBench (Vals AI) | Not measured | 38.1% | Only Qwen3.8 27B measured |
| CyberBench (Vals AI) | Not measured | 67.8% | Only Qwen3.8 27B measured |
| SciCode | 53.4% | 46.6% | MiniMax M3.1 Flash |
| LMArena Text: coding | Not measured | 1483 | Only Qwen3.8 27B measured |
| LMArena Text: software and IT | Not measured | 1478 | Only Qwen3.8 27B measured |
| LMArena WebDev: React | 1609 | 1602 | MiniMax M3.1 Flash |
| LMArena WebDev: HTML | 1529 | 1570 | Qwen3.8 27B |
| LMArena WebDev: from an image | Not measured | 1577 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 42.7 | 33.7 | MiniMax M3.1 Flash |
| Epoch Capabilities Index | Not measured | 151.7 | Only Qwen3.8 27B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 45.8 | Only Qwen3.8 27B measured |
| LiveBench research | 72.7% | 59.4% | MiniMax M3.1 Flash |
| LiveBench browser | 92.0% | 32.0% | MiniMax M3.1 Flash |
| LiveBench long agentic | 34.7% | 27.9% | MiniMax M3.1 Flash |
| Finance Agent (Vals AI) | Not measured | 48.5% | Only Qwen3.8 27B measured |
| Tax Agent Bench (Vals AI) | 32.1% | 30.9% | MiniMax M3.1 Flash |
| Legal Research Bench (Vals AI) | 34.1% | 36.1% | Qwen3.8 27B |
| Harvey's Legal Agent Benchmark (Vals AI) | 7.5% | Not measured | Only MiniMax M3.1 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 59.7% | Only Qwen3.8 27B measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only Qwen3.8 27B measured |
| APEX-Agents | Not measured | 47.5% | Only Qwen3.8 27B measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 88.9% | Only Qwen3.8 27B measured |
| LiveBench reasoning | 82.9% | 80.0% | MiniMax M3.1 Flash |
| MMMU Pro (Vals AI) | Not measured | 83.9% | Only Qwen3.8 27B measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 90.5% | Only Qwen3.8 27B measured |
| Humanity's Last Exam (Artificial Analysis run) | 48.0% | 33.9% | MiniMax M3.1 Flash |
| ARC-AGI | Not measured | 87.5% | Only Qwen3.8 27B measured |
| ARC-AGI-2 | Not measured | 42.4% | Only Qwen3.8 27B measured |
| LMArena Text: hard prompts | Not measured | 1459 | Only Qwen3.8 27B measured |
| LMArena Text: expert | Not measured | 1479 | Only Qwen3.8 27B measured |
| LMArena Text: hard prompts in English | Not measured | 1461 | Only Qwen3.8 27B measured |
| LMArena Vision: diagrams | Not measured | 1285 | Only Qwen3.8 27B measured |
| LMArena Vision: homework | Not measured | 1295 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | Leader |
|---|---|---|---|
| ProofBench | Not measured | 16.0% | Only Qwen3.8 27B measured |
| LMArena Text: math | Not measured | 1455 | Only Qwen3.8 27B measured |
| LMArena Text: mathematical work | Not measured | 1458 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 84.3% | Only Qwen3.8 27B measured |
| LegalBench (Vals AI) | Not measured | 82.4% | Only Qwen3.8 27B measured |
| TaxEval (Vals AI) | Not measured | 70.8% | Only Qwen3.8 27B measured |
| MortgageTax (Vals AI) | Not measured | 64.9% | Only Qwen3.8 27B measured |
| MedCode (Vals AI) | Not measured | 28.7% | Only Qwen3.8 27B measured |
| LMArena Text: science | Not measured | 1467 | Only Qwen3.8 27B measured |
| LMArena Text: medicine and healthcare | Not measured | 1437 | Only Qwen3.8 27B measured |
| LMArena Text: legal and government | Not measured | 1447 | Only Qwen3.8 27B measured |
| LMArena Text: business and finance | Not measured | 1438 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | Leader |
|---|---|---|---|
| LiveBench design | 74.0% | 75.9% | Qwen3.8 27B |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | Leader |
|---|---|---|---|
| Vals Index | 53.8% | Not measured | Only MiniMax M3.1 Flash measured |
| LiveBench data analysis | 71.4% | 76.6% | Qwen3.8 27B |
| SAGE (Vals AI) | Not measured | 52.4% | Only Qwen3.8 27B measured |
| MedScribe (Vals AI) | Not measured | 83.8% | Only Qwen3.8 27B measured |
| Long context reasoning (AA-LCR) | 79.7% | 82.0% | Qwen3.8 27B |
| DTBench | Not measured | 88.0% | Only Qwen3.8 27B measured |
| LMCA | Not measured | 41.4% | Only Qwen3.8 27B measured |
| Surface Evolver Bench | Not measured | 45.0% | Only Qwen3.8 27B measured |
| LMArena Text | Not measured | 1440 | Only Qwen3.8 27B measured |
| LMArena Text: instruction following | Not measured | 1436 | Only Qwen3.8 27B measured |
| LMArena Text: creative writing | Not measured | 1383 | Only Qwen3.8 27B measured |
| LMArena Vision | Not measured | 1269 | Only Qwen3.8 27B measured |
| LMArena Text: English | Not measured | 1448 | Only Qwen3.8 27B measured |
| LMArena Text: non-English | Not measured | 1428 | Only Qwen3.8 27B measured |
| LMArena Text: Chinese | Not measured | 1501 | Only Qwen3.8 27B measured |
| LMArena Text: German | Not measured | 1443 | Only Qwen3.8 27B measured |
| LMArena Text: Japanese | Not measured | 1387 | Only Qwen3.8 27B measured |
| LMArena Text: Korean | Not measured | 1384 | Only Qwen3.8 27B measured |
| LMArena Text: French | Not measured | 1465 | Only Qwen3.8 27B measured |
| LMArena Text: Spanish | Not measured | 1449 | Only Qwen3.8 27B measured |
| LMArena Text: Russian | Not measured | 1415 | Only Qwen3.8 27B measured |
| LMArena Text: Polish | Not measured | 1439 | Only Qwen3.8 27B measured |
| LMArena Text: multi-turn | Not measured | 1440 | Only Qwen3.8 27B measured |
| LMArena Text: longer queries | Not measured | 1448 | Only Qwen3.8 27B measured |
| LMArena Text: writing and language | Not measured | 1405 | Only Qwen3.8 27B measured |
| LMArena Text: entertainment and media | Not measured | 1393 | Only Qwen3.8 27B measured |
| LMArena Vision: English | Not measured | 1267 | Only Qwen3.8 27B measured |
| LMArena Vision: Chinese | Not measured | 1326 | Only Qwen3.8 27B measured |
| LMArena Vision: reading text | Not measured | 1281 | Only Qwen3.8 27B measured |
| LMArena Vision: humor | Not measured | 1235 | Only Qwen3.8 27B measured |
| LMArena Vision: creative writing | Not measured | 1237 | Only Qwen3.8 27B measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M3.1 Flash | Qwen3.8 27B | 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
MiniMax M3.1 Flash costs less
Repository review
50K input + 3K output tokens
MiniMax M3.1 Flash costs less
Agent loop
200K input + 10K output tokens
MiniMax M3.1 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 | MiniMax M3.1 Flash | Qwen3.8 27B |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 19, 2026 | August 14, 2026 |
| Context window | 1M | 1M |
| Input $/Mtok | $0.15 | $0.425 |
| Output $/Mtok | $0.60 | $2.55 |
| Coding index | 59.0 | 74.2 |
| Independent measurements behind it | 4 | 4 |
| Cost per solved task | Not computable | $1.26 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M3.1 Flash better than Qwen3.8 27B for coding?
Pick Qwen3.8 27B for coding: it scores 74.2 on the Vibe Coding Index against 59.0 for MiniMax M3.1 Flash. Pick MiniMax M3.1 Flash for output tokens 4.3x cheaper ($0.60 vs $2.55 per million) and work measured by Vibe Code Bench (Vals AI) or SciCode, where it leads.
Which is cheaper, MiniMax M3.1 Flash or Qwen3.8 27B?
MiniMax M3.1 Flash costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3.8 27B costs $0.425 and $2.55. Cost per solved task is known for Qwen3.8 27B only.
Which has the bigger context window, MiniMax M3.1 Flash or Qwen3.8 27B?
Neither: both take 1M tokens.
How many benchmarks is the MiniMax M3.1 Flash vs Qwen3.8 27B comparison based on?
17 benchmarks have a result for both models as of October 22, 2026. MiniMax M3.1 Flash's coding index rests on 4 independent benchmarks and Qwen3.8 27B's on 4. Where only one model has a result, the page says so instead of naming a winner.