MiniMax M3 vs Qwen3.6 27B
MiniMax M3 leads Qwen3.6 27B on coding, 39.2 to 36.8 on the Vibe Coding Index, and MiniMax M3 costs 2.3x less per output token ($1.20 vs $2.70 per million). Updated October 23, 2026; 23 benchmarks have a result for both.
MiniMax M3 or Qwen3.6 27B: which to pick
Pick MiniMax M3 for coding: it scores 39.2 on the Vibe Coding Index against 36.8 for Qwen3.6 27B.
Pick Qwen3.6 27B for work measured by τ²-Bench Telecom or OTIS Mock AIME, where it leads.
- Shared results
- 23
- MiniMax M3 only
- 94
- Qwen3.6 27B only
- 2
- Like-for-like categories
- 7 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
MiniMax M3
MiniMax M3 scores 39.2 against 36.8.
6 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiniMax M3
MiniMax M3 leads, 29.2 against 21.4.
Same board, both measured
Agentic work
AA Agentic Index
MiniMax M3
MiniMax M3 leads, 29.5 against 18.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only MiniMax M3 has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M3 has a MMLU Pro result, 84.2%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M3 has a Design Arena: websites result, 1257.
Directional only
Long documents
Listed context window
MiniMax M3
MiniMax M3 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M3
MiniMax M3 $0.0009, Qwen3.6 27B $0.0018 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
MiniMax M3
MiniMax M3 $0.56, Qwen3.6 27B $1.30.
Published attempt cost and pass rate
At a glance
- Coding index
- MiniMax M3 39.2 from 6 benchmarks, Qwen3.6 27B 36.8 from 2 benchmarks.
- Widest category
- Math, 20.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): MiniMax M3 47.6% against Qwen3.6 27B 11.9%, 35.6 points apart on a 0 to 100 scale.
- Output price
- MiniMax M3 $1.20 against Qwen3.6 27B $2.70 per million output tokens, 2.3x apart.
- Context window
- MiniMax M3 takes 1.05M tokens, Qwen3.6 27B 262K.
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 | Bars | Qwen3.6 27B | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 1 | ||
| Reasoning | 4 | 0 | ||
| Math | 0 | 1 | ||
| Knowledge | 3 | 0 | ||
| General | 5 | 1 | ||
| All shared boards | 20 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index50
| Benchmark | MiniMax M3 | Qwen3.6 27B | Leader |
|---|---|---|---|
| LiveBench coding | 70.9% | Not measured | Only MiniMax M3 measured |
| LMArena WebDev | 1482 | Not measured | Only MiniMax M3 measured |
| AA Coding Index | 58.6 | 53.7 | MiniMax M3 |
| LiveCodeBench (Vals AI) | 82.2% | Not measured | Only MiniMax M3 measured |
| SWE-bench Verified (Vals AI) | 75.0% | 70.0% | MiniMax M3 |
| Terminal-Bench 4 (Vals AI) | 1.0% | Not measured | Only MiniMax M3 measured |
| Vibe Code Bench (Vals AI) | 47.6% | 11.9% | MiniMax M3 |
| Code migration (Vals AI) | 19.9% | Not measured | Only MiniMax M3 measured |
| Terminal-Bench 2.1 (Vals AI) | 53.6% | Not measured | Only MiniMax M3 measured |
| SWE-bench Multimodal (Vals AI) | 33.3% | Not measured | Only MiniMax M3 measured |
| Vibe Code Bench 1-100 (Vals AI) | 9.2% | Not measured | Only MiniMax M3 measured |
| SkillsBench (Vals AI) | 51.5% | Not measured | Only MiniMax M3 measured |
| CyberBench (Vals AI) | 65.0% | Not measured | Only MiniMax M3 measured |
| SciCode | 47.1% | 42.8% | MiniMax M3 |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | 34.8% | MiniMax M3 |
| FrontierCode | 14.7% | Not measured | Only MiniMax M3 measured |
| ALE-Bench | 640.0 | Not measured | Only MiniMax M3 measured |
| LMArena Text: coding | 1470 | Not measured | Only MiniMax M3 measured |
| LMArena Text: software and IT | 1466 | Not measured | Only MiniMax M3 measured |
| LMArena WebDev: React | 1478 | Not measured | Only MiniMax M3 measured |
| LMArena WebDev: HTML | 1454 | Not measured | Only MiniMax M3 measured |
| LMArena WebDev: from an image | 1470 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M3 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 29.2 | 21.4 | MiniMax M3 |
| Epoch Capabilities Index | 146.9 | 146.2 | MiniMax M3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | MiniMax M3 | Qwen3.6 27B | Leader |
|---|---|---|---|
| AA Agentic Index | 29.5 | 18.5 | MiniMax M3 |
| Design Arena: agents building web apps | 1200 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building full-stack apps | 1197 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building mobile apps | 1169 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building Android apps | 1160 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building games | 1159 | Not measured | Only MiniMax M3 measured |
| Design Arena: HTML slides | 1086 | Not measured | Only MiniMax M3 measured |
| Design Arena: PowerPoint slides | 1169 | Not measured | Only MiniMax M3 measured |
| Design Arena: spreadsheets | 1042 | Not measured | Only MiniMax M3 measured |
| LiveBench research | 68.0% | Not measured | Only MiniMax M3 measured |
| LiveBench browser | 8.0% | Not measured | Only MiniMax M3 measured |
| LiveBench long agentic | 12.4% | Not measured | Only MiniMax M3 measured |
| Finance Agent (Vals AI) | 48.3% | Not measured | Only MiniMax M3 measured |
| Tax Agent Bench (Vals AI) | 20.6% | Not measured | Only MiniMax M3 measured |
| Legal Research Bench (Vals AI) | 29.8% | Not measured | Only MiniMax M3 measured |
| Excel Modeling Benchmark (Vals AI) | 47.8% | Not measured | Only MiniMax M3 measured |
| τ²-Bench Telecom | 88.9% | 94.2% | Qwen3.6 27B |
| APEX-Agents | 37.7% | Not measured | Only MiniMax M3 measured |
| OSWorld 2.0 | 4.6% | Not measured | Only MiniMax M3 measured |
| Vending-Bench 2 | $2,158 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | MiniMax M3 | Qwen3.6 27B | Leader |
|---|---|---|---|
| GPQA Diamond | 92.7% | Not measured | Only MiniMax M3 measured |
| LiveBench reasoning | 74.5% | Not measured | Only MiniMax M3 measured |
| MMMU Pro (Vals AI) | 81.2% | Not measured | Only MiniMax M3 measured |
| GPQA Diamond (Artificial Analysis run) | 92.9% | 84.2% | MiniMax M3 |
| Humanity's Last Exam (Artificial Analysis run) | 39.0% | 23.1% | MiniMax M3 |
| GPQA Diamond (Epoch AI run) | 90.9% | 85.9% | MiniMax M3 |
| SimpleBench | 45.8% | Not measured | Only MiniMax M3 measured |
| Chess puzzles | 13.0% | Not measured | Only MiniMax M3 measured |
| Mystery game puzzles | 8.0% | 7.0% | MiniMax M3 |
| LMArena Text: hard prompts | 1447 | Not measured | Only MiniMax M3 measured |
| LMArena Text: expert | 1461 | Not measured | Only MiniMax M3 measured |
| LMArena Text: hard prompts in English | 1455 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: diagrams | 1266 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: homework | 1268 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | MiniMax M3 | Qwen3.6 27B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 71.1% | 91.1% | Qwen3.6 27B |
| FrontierMath, tiers 1 to 3 | Not measured | 35.1% | Only Qwen3.6 27B measured |
| ProofBench | 18.0% | Not measured | Only MiniMax M3 measured |
| LMArena Text: math | 1429 | Not measured | Only MiniMax M3 measured |
| LMArena Text: mathematical work | 1448 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | MiniMax M3 | Qwen3.6 27B | Leader |
|---|---|---|---|
| MMLU Pro | 84.2% | Not measured | Only MiniMax M3 measured |
| LegalBench (Vals AI) | 85.4% | Not measured | Only MiniMax M3 measured |
| CaseLaw (Vals AI) | Not measured | 53.2% | Only Qwen3.6 27B measured |
| CorpFin (Vals AI) | 68.1% | 62.3% | MiniMax M3 |
| TaxEval (Vals AI) | 72.7% | 71.3% | MiniMax M3 |
| MortgageTax (Vals AI) | 68.4% | 68.3% | MiniMax M3 |
| MedCode (Vals AI) | 46.3% | Not measured | Only MiniMax M3 measured |
| LMArena Text: science | 1451 | Not measured | Only MiniMax M3 measured |
| LMArena Text: medicine and healthcare | 1439 | Not measured | Only MiniMax M3 measured |
| LMArena Text: legal and government | 1436 | Not measured | Only MiniMax M3 measured |
| LMArena Text: business and finance | 1434 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | MiniMax M3 | Qwen3.6 27B | Leader |
|---|---|---|---|
| Design Arena: websites | 1257 | Not measured | Only MiniMax M3 measured |
| Design Arena: UI components | 1243 | Not measured | Only MiniMax M3 measured |
| Design Arena: game dev | 1211 | Not measured | Only MiniMax M3 measured |
| Design Arena: data viz | 1236 | Not measured | Only MiniMax M3 measured |
| Design Arena: 3D | 1209 | Not measured | Only MiniMax M3 measured |
| Design Arena: all code categories | 1246 | Not measured | Only MiniMax M3 measured |
| Design Arena: SVG | 1161 | Not measured | Only MiniMax M3 measured |
| Design Arena: ASCII art | 1161 | Not measured | Only MiniMax M3 measured |
| LiveBench design | 66.2% | Not measured | Only MiniMax M3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index51
| Benchmark | MiniMax M3 | Qwen3.6 27B | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.2% | Not measured | Only MiniMax M3 measured |
| Public Benefits Bench (Vals AI) | 64.1% | Not measured | Only MiniMax M3 measured |
| SAGE (Vals AI) | 50.6% | 45.6% | MiniMax M3 |
| MedScribe (Vals AI) | 87.3% | Not measured | Only MiniMax M3 measured |
| Vals Multimodal Index | 60.0% | Not measured | Only MiniMax M3 measured |
| IFBench | 82.9% | 67.6% | MiniMax M3 |
| Long context reasoning (AA-LCR) | 83.0% | 77.3% | MiniMax M3 |
| DTBench | 78.9% | 78.1% | MiniMax M3 |
| LMCA | 33.7% | 34.5% | Qwen3.6 27B |
| Surface Evolver Bench | 55.0% | Not measured | Only MiniMax M3 measured |
| LMArena Text | 1432 | Not measured | Only MiniMax M3 measured |
| LMArena Text: instruction following | 1432 | Not measured | Only MiniMax M3 measured |
| LMArena Text: creative writing | 1403 | Not measured | Only MiniMax M3 measured |
| LMArena Vision | 1251 | Not measured | Only MiniMax M3 measured |
| LMArena Text: English | 1442 | Not measured | Only MiniMax M3 measured |
| LMArena Text: non-English | 1419 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Chinese | 1465 | Not measured | Only MiniMax M3 measured |
| LMArena Text: German | 1430 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Japanese | 1379 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Korean | 1372 | Not measured | Only MiniMax M3 measured |
| LMArena Text: French | 1443 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Spanish | 1432 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Russian | 1427 | Not measured | Only MiniMax M3 measured |
| LMArena Text: Polish | 1425 | Not measured | Only MiniMax M3 measured |
| LMArena Text: multi-turn | 1443 | Not measured | Only MiniMax M3 measured |
| LMArena Text: longer queries | 1445 | Not measured | Only MiniMax M3 measured |
| LMArena Text: writing and language | 1418 | Not measured | Only MiniMax M3 measured |
| LMArena Text: entertainment and media | 1402 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: English | 1263 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: Chinese | 1311 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: reading text | 1259 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: humor | 1235 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: recognizing things | 1197 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: creative writing | 1234 | Not measured | Only MiniMax M3 measured |
| LMArena Document | 1435 | Not measured | Only MiniMax M3 measured |
| EQ-Bench 4 | 1150 | 1026 | MiniMax M3 |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M3 | Qwen3.6 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 costs less
Repository review
50K input + 3K output tokens
MiniMax M3 costs less
Agent loop
200K input + 10K output tokens
MiniMax M3 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 | Qwen3.6 27B |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | Open weights | Open weights |
| Released | May 31, 2026 | April 27, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.30 | $0.45 |
| Output $/Mtok | $1.20 | $2.70 |
| Coding index | 39.2 | 36.8 |
| Independent measurements behind it | 6 | 2 |
| Cost per solved task | $0.56 | $1.30 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M3 better than Qwen3.6 27B for coding?
Pick MiniMax M3 for coding: it scores 39.2 on the Vibe Coding Index against 36.8 for Qwen3.6 27B. Pick Qwen3.6 27B for work measured by τ²-Bench Telecom or OTIS Mock AIME, where it leads.
Which is cheaper, MiniMax M3 or Qwen3.6 27B?
MiniMax M3 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3.6 27B costs $0.45 and $2.70. Per solved SWE-bench Verified task, MiniMax M3 costs $0.56 and Qwen3.6 27B $1.30.
Which has the bigger context window, MiniMax M3 or Qwen3.6 27B?
MiniMax M3, with 1.05M tokens against 262K.
How many benchmarks is the MiniMax M3 vs Qwen3.6 27B comparison based on?
23 benchmarks have a result for both models as of October 23, 2026. MiniMax M3's coding index rests on 6 independent benchmarks and Qwen3.6 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.