MiniMax M3 vs Qwen3.7 Plus
MiniMax M3 leads Qwen3.7 Plus on coding, 39.2 to 33.2 on the Vibe Coding Index, at about the same output price ($1.20 vs $1.28 per million). Updated October 22, 2026; 74 benchmarks have a result for both.
MiniMax M3 or Qwen3.7 Plus: which to pick
Pick MiniMax M3 for coding: it scores 39.2 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus.
Pick Qwen3.7 Plus for work measured by SkillsBench (Vals AI) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 74
- MiniMax M3 only
- 42
- Qwen3.7 Plus only
- 1
- 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
MiniMax M3
MiniMax M3 scores 39.2 against 33.2.
6 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiniMax M3
MiniMax M3 leads, 29.2 against 25.2.
Same board, both measured
Agentic work
AA Agentic Index
MiniMax M3
MiniMax M3 leads, 29.5 against 17.5.
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
Qwen3.7 Plus
Qwen3.7 Plus leads, 1269 against 1257.
Same board, both measured
Long documents
Listed context window
MiniMax M3
MiniMax M3 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M3
MiniMax M3 $0.0009, Qwen3.7 Plus $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M3 has the number, $0.56.
Directional only
At a glance
- Coding index
- MiniMax M3 39.2 from 6 benchmarks, Qwen3.7 Plus 33.2 from 2 benchmarks.
- Widest category
- Math, 10.7 points apart on average over 3 shared benchmarks.
- Widest single gap
- OTIS Mock AIME: MiniMax M3 71.1% against Qwen3.7 Plus 93.3%, 22.2 points apart on a 0 to 100 scale.
- Output price
- MiniMax M3 $1.20 against Qwen3.7 Plus $1.28 per million output tokens, 1.1x apart.
- Context window
- MiniMax M3 takes 1.05M tokens, Qwen3.7 Plus 1M.
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 | Qwen3.7 Plus | Ties |
|---|---|---|---|---|
| Coding | 6 | 4 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 5 | 2 | ||
| Reasoning | 3 | 6 | ||
| Math | 0 | 3 | ||
| Knowledge | 1 | 4 | ||
| Web design | 1 | 7 | ||
| General | 4 | 26 | ||
| All shared boards | 21 | 53 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index64
| Benchmark | MiniMax M3 | Qwen3.7 Plus | 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 | 55.9 | MiniMax M3 |
| LiveCodeBench (Vals AI) | 82.2% | Not measured | Only MiniMax M3 measured |
| SWE-bench Verified (Vals AI) | 75.0% | Not measured | Only MiniMax M3 measured |
| Terminal-Bench 4 (Vals AI) | 1.0% | Not measured | Only MiniMax M3 measured |
| Vibe Code Bench (Vals AI) | 47.6% | 46.4% | MiniMax M3 |
| Code migration (Vals AI) | 19.9% | 12.9% | MiniMax M3 |
| Terminal-Bench 2.1 (Vals AI) | 53.6% | 52.8% | MiniMax M3 |
| 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% | 54.3% | Qwen3.7 Plus |
| CyberBench (Vals AI) | 65.0% | Not measured | Only MiniMax M3 measured |
| SciCode | 47.1% | 46.1% | MiniMax M3 |
| Terminal-Bench Hard (Artificial Analysis run) | 42.4% | 47.0% | Qwen3.7 Plus |
| FrontierCode | 14.7% | 10.2% | MiniMax M3 |
| ALE-Bench | 640.0 | Not measured | Only MiniMax M3 measured |
| LMArena Text: coding | 1470 | 1473 | Qwen3.7 Plus |
| LMArena Text: software and IT | 1466 | 1473 | Qwen3.7 Plus |
| LMArena WebDev: React | 1478 | Not measured | Only MiniMax M3 measured |
| LMArena WebDev: HTML | 1455 | 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 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | MiniMax M3 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 29.2 | 25.2 | MiniMax M3 |
| Epoch Capabilities Index | 146.9 | 147.0 | Qwen3.7 Plus |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index52
| Benchmark | MiniMax M3 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | 29.5 | 17.5 | 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 | 1159 | Not measured | Only MiniMax M3 measured |
| Design Arena: agents building games | 1158 | Not measured | Only MiniMax M3 measured |
| Design Arena: HTML slides | 1130 | Not measured | Only MiniMax M3 measured |
| Design Arena: PowerPoint slides | 1181 | Not measured | Only MiniMax M3 measured |
| Design Arena: spreadsheets | 1028 | 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% | 38.2% | MiniMax M3 |
| Tax Agent Bench (Vals AI) | 20.6% | 10.5% | MiniMax M3 |
| Legal Research Bench (Vals AI) | 29.8% | 16.4% | MiniMax M3 |
| Excel Modeling Benchmark (Vals AI) | 47.8% | 49.3% | Qwen3.7 Plus |
| τ²-Bench Telecom | 88.9% | 93.0% | Qwen3.7 Plus |
| APEX-Agents | 37.7% | Not measured | Only MiniMax M3 measured |
| OSWorld 2.0 | 4.6% | 2.8% | MiniMax M3 |
| Vending-Bench 2 | $2,158 | Not measured | Only MiniMax M3 measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index36
| Benchmark | MiniMax M3 | Qwen3.7 Plus | 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% | 90.0% | MiniMax M3 |
| Humanity's Last Exam (Artificial Analysis run) | 39.0% | 35.6% | MiniMax M3 |
| GPQA Diamond (Epoch AI run) | 90.9% | 87.9% | 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% | 17.0% | Qwen3.7 Plus |
| LMArena Text: hard prompts | 1447 | 1460 | Qwen3.7 Plus |
| LMArena Text: expert | 1461 | 1466 | Qwen3.7 Plus |
| LMArena Text: hard prompts in English | 1455 | 1460 | Qwen3.7 Plus |
| LMArena Vision: diagrams | 1266 | 1292 | Qwen3.7 Plus |
| LMArena Vision: homework | 1268 | 1295 | Qwen3.7 Plus |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | MiniMax M3 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| OTIS Mock AIME | 71.1% | 93.3% | Qwen3.7 Plus |
| FrontierMath, tiers 1 to 3 | Not measured | 34.4% | Only Qwen3.7 Plus measured |
| ProofBench | 18.0% | Not measured | Only MiniMax M3 measured |
| LMArena Text: math | 1429 | 1467 | Qwen3.7 Plus |
| LMArena Text: mathematical work | 1448 | 1470 | Qwen3.7 Plus |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
| Benchmark | MiniMax M3 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| MMLU Pro | 84.2% | Not measured | Only MiniMax M3 measured |
| LegalBench (Vals AI) | 85.4% | Not measured | Only MiniMax M3 measured |
| CorpFin (Vals AI) | 68.1% | Not measured | Only MiniMax M3 measured |
| TaxEval (Vals AI) | 72.7% | Not measured | Only MiniMax M3 measured |
| MortgageTax (Vals AI) | 68.4% | 66.2% | MiniMax M3 |
| MedCode (Vals AI) | 46.3% | Not measured | Only MiniMax M3 measured |
| LMArena Text: science | 1452 | 1464 | Qwen3.7 Plus |
| LMArena Text: medicine and healthcare | 1441 | 1464 | Qwen3.7 Plus |
| LMArena Text: legal and government | 1437 | 1451 | Qwen3.7 Plus |
| LMArena Text: business and finance | 1434 | 1435 | Qwen3.7 Plus |
| Neither model has a result on the other 8 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index17
| Benchmark | MiniMax M3 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 1257 | 1269 | Qwen3.7 Plus |
| Design Arena: UI components | 1242 | 1258 | Qwen3.7 Plus |
| Design Arena: game dev | 1210 | 1261 | Qwen3.7 Plus |
| Design Arena: data viz | 1236 | 1276 | Qwen3.7 Plus |
| Design Arena: 3D | 1208 | 1238 | Qwen3.7 Plus |
| Design Arena: all code categories | 1247 | 1269 | Qwen3.7 Plus |
| Design Arena: SVG | 1161 | 1208 | Qwen3.7 Plus |
| Design Arena: ASCII art | 1161 | 1143 | MiniMax M3 |
| LiveBench design | 66.2% | Not measured | Only MiniMax M3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index426
| Benchmark | MiniMax M3 | Qwen3.7 Plus | 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% | 39.3% | MiniMax M3 |
| MedScribe (Vals AI) | 87.3% | Not measured | Only MiniMax M3 measured |
| Vals Multimodal Index | 60.0% | 53.9% | MiniMax M3 |
| IFBench | 82.9% | 78.0% | MiniMax M3 |
| Long context reasoning (AA-LCR) | 83.0% | 73.0% | MiniMax M3 |
| DTBench | 78.9% | 84.0% | Qwen3.7 Plus |
| LMCA | 33.7% | 37.6% | Qwen3.7 Plus |
| Surface Evolver Bench | 55.0% | Not measured | Only MiniMax M3 measured |
| LMArena Text | 1433 | 1454 | Qwen3.7 Plus |
| LMArena Text: instruction following | 1433 | 1439 | Qwen3.7 Plus |
| LMArena Text: creative writing | 1404 | 1438 | Qwen3.7 Plus |
| LMArena Vision | 1251 | 1278 | Qwen3.7 Plus |
| LMArena Text: English | 1443 | 1458 | Qwen3.7 Plus |
| LMArena Text: non-English | 1420 | 1445 | Qwen3.7 Plus |
| LMArena Text: Chinese | 1466 | 1509 | Qwen3.7 Plus |
| LMArena Text: German | 1428 | 1471 | Qwen3.7 Plus |
| LMArena Text: Japanese | 1380 | 1412 | Qwen3.7 Plus |
| LMArena Text: Korean | 1373 | 1413 | Qwen3.7 Plus |
| LMArena Text: French | 1444 | 1472 | Qwen3.7 Plus |
| LMArena Text: Spanish | 1433 | 1457 | Qwen3.7 Plus |
| LMArena Text: Russian | 1426 | 1457 | Qwen3.7 Plus |
| LMArena Text: Polish | 1423 | 1449 | Qwen3.7 Plus |
| LMArena Text: multi-turn | 1443 | 1459 | Qwen3.7 Plus |
| LMArena Text: longer queries | 1446 | 1454 | Qwen3.7 Plus |
| LMArena Text: writing and language | 1419 | 1437 | Qwen3.7 Plus |
| LMArena Text: entertainment and media | 1403 | 1422 | Qwen3.7 Plus |
| LMArena Vision: English | 1263 | 1280 | Qwen3.7 Plus |
| LMArena Vision: Chinese | 1311 | 1332 | Qwen3.7 Plus |
| LMArena Vision: reading text | 1259 | 1288 | Qwen3.7 Plus |
| LMArena Vision: humor | 1235 | 1261 | Qwen3.7 Plus |
| LMArena Vision: recognizing things | 1197 | Not measured | Only MiniMax M3 measured |
| LMArena Vision: creative writing | 1234 | 1258 | Qwen3.7 Plus |
| LMArena Document | 1435 | 1444 | Qwen3.7 Plus |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M3 | Qwen3.7 Plus | 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 | Qwen3.7 Plus |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | Open weights | No public weights listed |
| Released | May 31, 2026 | June 3, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $0.30 | $0.32 |
| Output $/Mtok | $1.20 | $1.28 |
| Coding index | 39.2 | 33.2 |
| Independent measurements behind it | 6 | 2 |
| Cost per solved task | $0.56 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M3 better than Qwen3.7 Plus for coding?
Pick MiniMax M3 for coding: it scores 39.2 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus. Pick Qwen3.7 Plus for work measured by SkillsBench (Vals AI) or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, MiniMax M3 or Qwen3.7 Plus?
MiniMax M3 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for MiniMax M3 only.
Which has the bigger context window, MiniMax M3 or Qwen3.7 Plus?
MiniMax M3, with 1.05M tokens against 1M.
How many benchmarks is the MiniMax M3 vs Qwen3.7 Plus comparison based on?
74 benchmarks have a result for both models as of October 22, 2026. MiniMax M3's coding index rests on 6 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.