MiniMax M1 vs Qwen3.7 Max
Qwen3.7 Max leads MiniMax M1 on the Artificial Analysis Intelligence Index, 29.5 to 11.7, and MiniMax M1 costs 2.0x less per output token ($2.20 vs $4.425 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
MiniMax M1 or Qwen3.7 Max: which to pick
Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; MiniMax M1 has none, so the two cannot be ranked on coding.
Pick MiniMax M1 for output tokens 2.0x cheaper ($2.20 vs $4.425 per million).
- Shared results
- 1
- MiniMax M1 only
- 28
- Qwen3.7 Max only
- 59
- Like-for-like categories
- 1 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
No call
Only Qwen3.7 Max has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.7 Max
Qwen3.7 Max leads, 29.5 against 11.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Max has a AA Agentic Index result, 22.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.7 Max has a GPQA Diamond result, 90.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.7 Max has a MMLU Pro result, 89.3%.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.7 Max has a Design Arena: websites result, 1274.
Directional only
Long documents
Listed context window
No call
Both take 1M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M1
MiniMax M1 $0.0015, Qwen3.7 Max $0.0037 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.7 Max has the number, $4.69.
Directional only
At a glance
- Coding index
- MiniMax M1 not benchmarked, Qwen3.7 Max 54.1 from 3 benchmarks.
- Widest category
- Intelligence, 17.8 points apart on average over 1 shared benchmark.
- Widest single gap
- AA Intelligence Index: MiniMax M1 11.7 against Qwen3.7 Max 29.5, 17.8 points apart on a 0 to 100 scale.
- Output price
- MiniMax M1 $2.20 against Qwen3.7 Max $4.425 per million output tokens, 2.0x 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 M1 | Bars | Qwen3.7 Max | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| All shared boards | 0 | 1 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index14 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.7 Max | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1515 | Only Qwen3.7 Max measured |
| AA Coding Index | Not measured | 66.0 | Only Qwen3.7 Max measured |
| LiveCodeBench (Vals AI) | Not measured | 87.1% | Only Qwen3.7 Max measured |
| SWE-bench Verified (Vals AI) | Not measured | 68.8% | Only Qwen3.7 Max measured |
| Vibe Code Bench (Vals AI) | Not measured | 47.7% | Only Qwen3.7 Max measured |
| Code migration (Vals AI) | Not measured | 13.1% | Only Qwen3.7 Max measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 61.0% | Only Qwen3.7 Max measured |
| SciCode | Not measured | 49.5% | Only Qwen3.7 Max measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only Qwen3.7 Max measured |
| ALE-Bench | Not measured | 1189.4 | Only Qwen3.7 Max measured |
| LMArena Text: coding | 1359 | Not measured | Only MiniMax M1 measured |
| LMArena Text: software and IT | 1359 | Not measured | Only MiniMax M1 measured |
| LMArena WebDev: React | Not measured | 1514 | Only Qwen3.7 Max measured |
| LMArena WebDev: HTML | Not measured | 1512 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | MiniMax M1 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.7 | 29.5 | Qwen3.7 Max |
| Epoch Capabilities Index | Not measured | 154.0 | Only Qwen3.7 Max measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.7 Max | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 22.5 | Only Qwen3.7 Max measured |
| Design Arena: agents building web apps | Not measured | 1208 | Only Qwen3.7 Max measured |
| Design Arena: agents building full-stack apps | Not measured | 1191 | Only Qwen3.7 Max measured |
| Design Arena: agents building mobile apps | Not measured | 1154 | Only Qwen3.7 Max measured |
| Design Arena: agents building Android apps | Not measured | 1159 | Only Qwen3.7 Max measured |
| Design Arena: agents building Godot games | Not measured | 1187 | Only Qwen3.7 Max measured |
| Design Arena: agents building games | Not measured | 1161 | Only Qwen3.7 Max measured |
| Design Arena: HTML slides | Not measured | 1098 | Only Qwen3.7 Max measured |
| Design Arena: PowerPoint slides | Not measured | 1169 | Only Qwen3.7 Max measured |
| Finance Agent (Vals AI) | Not measured | 47.8% | Only Qwen3.7 Max measured |
| Tax Agent Bench (Vals AI) | Not measured | 15.8% | Only Qwen3.7 Max measured |
| Legal Research Bench (Vals AI) | Not measured | 25.5% | Only Qwen3.7 Max measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 57.0% | Only Qwen3.7 Max measured |
| τ²-Bench Telecom | Not measured | 94.7% | Only Qwen3.7 Max measured |
| Neither model has a result on the other 28 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.7 Max | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 90.2% | Only Qwen3.7 Max measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 92.3% | Only Qwen3.7 Max measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 40.5% | Only Qwen3.7 Max measured |
| GPQA Diamond (Epoch AI run) | Not measured | 90.9% | Only Qwen3.7 Max measured |
| SimpleBench | Not measured | 70.4% | Only Qwen3.7 Max measured |
| Chess puzzles | Not measured | 26.0% | Only Qwen3.7 Max measured |
| Mystery game puzzles | Not measured | 32.0% | Only Qwen3.7 Max measured |
| EBR-bench | Not measured | 9.5% | Only Qwen3.7 Max measured |
| LMArena Text: hard prompts | 1339 | Not measured | Only MiniMax M1 measured |
| LMArena Text: expert | 1317 | Not measured | Only MiniMax M1 measured |
| LMArena Text: hard prompts in English | 1353 | Not measured | Only MiniMax M1 measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.7 Max | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 95.6% | Only Qwen3.7 Max measured |
| FrontierMath, tiers 1 to 3 | Not measured | 64.6% | Only Qwen3.7 Max measured |
| FrontierMath, tier 4 | Not measured | 34.1% | Only Qwen3.7 Max measured |
| ProofBench | Not measured | 26.0% | Only Qwen3.7 Max measured |
| LMArena Text: math | 1361 | Not measured | Only MiniMax M1 measured |
| LMArena Text: mathematical work | 1363 | Not measured | Only MiniMax M1 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.7 Max | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 89.3% | Only Qwen3.7 Max measured |
| LegalBench (Vals AI) | Not measured | 84.9% | Only Qwen3.7 Max measured |
| CorpFin (Vals AI) | Not measured | 63.7% | Only Qwen3.7 Max measured |
| TaxEval (Vals AI) | Not measured | 75.3% | Only Qwen3.7 Max measured |
| MedCode (Vals AI) | Not measured | 38.8% | Only Qwen3.7 Max measured |
| SimpleQA Verified | Not measured | 55.8% | Only Qwen3.7 Max measured |
| LMArena Text: science | 1354 | Not measured | Only MiniMax M1 measured |
| LMArena Text: medicine and healthcare | 1355 | Not measured | Only MiniMax M1 measured |
| LMArena Text: legal and government | 1337 | Not measured | Only MiniMax M1 measured |
| LMArena Text: business and finance | 1319 | Not measured | Only MiniMax M1 measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.7 Max | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1274 | Only Qwen3.7 Max measured |
| Design Arena: UI components | Not measured | 1267 | Only Qwen3.7 Max measured |
| Design Arena: game dev | Not measured | 1265 | Only Qwen3.7 Max measured |
| Design Arena: data viz | Not measured | 1276 | Only Qwen3.7 Max measured |
| Design Arena: 3D | Not measured | 1265 | Only Qwen3.7 Max measured |
| Design Arena: all code categories | Not measured | 1275 | Only Qwen3.7 Max measured |
| Design Arena: SVG | Not measured | 1216 | Only Qwen3.7 Max measured |
| Design Arena: ASCII art | Not measured | 1211 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index23 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.7 Max | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | Not measured | 79.4% | Only Qwen3.7 Max measured |
| IFBench | Not measured | 80.5% | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | Not measured | 79.0% | Only Qwen3.7 Max measured |
| DTBench | Not measured | 92.3% | Only Qwen3.7 Max measured |
| LMCA | Not measured | 44.0% | Only Qwen3.7 Max measured |
| LMArena Text | 1343 | Not measured | Only MiniMax M1 measured |
| LMArena Text: instruction following | 1312 | Not measured | Only MiniMax M1 measured |
| LMArena Text: creative writing | 1297 | Not measured | Only MiniMax M1 measured |
| LMArena Text: English | 1363 | Not measured | Only MiniMax M1 measured |
| LMArena Text: non-English | 1319 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Chinese | 1360 | Not measured | Only MiniMax M1 measured |
| LMArena Text: German | 1350 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Japanese | 1217 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Korean | 1266 | Not measured | Only MiniMax M1 measured |
| LMArena Text: French | 1370 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Spanish | 1353 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Russian | 1329 | Not measured | Only MiniMax M1 measured |
| LMArena Text: Polish | 1329 | Not measured | Only MiniMax M1 measured |
| LMArena Text: multi-turn | 1335 | Not measured | Only MiniMax M1 measured |
| LMArena Text: longer queries | 1326 | Not measured | Only MiniMax M1 measured |
| LMArena Text: writing and language | 1311 | Not measured | Only MiniMax M1 measured |
| LMArena Text: entertainment and media | 1303 | Not measured | Only MiniMax M1 measured |
| EQ-Bench 4 | Not measured | 1110 | Only Qwen3.7 Max measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.7 Max | 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 M1 costs less
Repository review
50K input + 3K output tokens
MiniMax M1 costs less
Agent loop
200K input + 10K output tokens
MiniMax M1 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 M1 | Qwen3.7 Max |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | May 21, 2026 |
| Context window | 1M | 1M |
| Input $/Mtok | $0.40 | $1.475 |
| Output $/Mtok | $2.20 | $4.425 |
| Coding index | Not benchmarked | 54.1 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $4.69 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M1 better than Qwen3.7 Max for coding?
Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; MiniMax M1 has none, so the two cannot be ranked on coding. Pick MiniMax M1 for output tokens 2.0x cheaper ($2.20 vs $4.425 per million).
Which is cheaper, MiniMax M1 or Qwen3.7 Max?
MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens; Qwen3.7 Max costs $1.475 and $4.425. Cost per solved task is known for Qwen3.7 Max only.
Which has the bigger context window, MiniMax M1 or Qwen3.7 Max?
Neither: both take 1M tokens.
How many benchmarks is the MiniMax M1 vs Qwen3.7 Max comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. MiniMax M1's coding index rests on 0 independent benchmarks and Qwen3.7 Max's on 3. Where only one model has a result, the page says so instead of naming a winner.