MiniMax M1 vs Qwen3.5 397B A17B
Qwen3.5 397B A17B leads MiniMax M1 on the Artificial Analysis Intelligence Index, 21.4 to 11.7, at about the same output price ($2.34 vs $2.20 per million). Updated October 22, 2026; 29 benchmarks have a result for both.
MiniMax M1 or Qwen3.5 397B A17B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick MiniMax M1 for output tokens 1.1x cheaper ($2.20 vs $2.34 per million) and a larger context window (1M against 262K tokens).
- Shared results
- 29
- MiniMax M1 only
- 0
- Qwen3.5 397B A17B only
- 37
- 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.5 397B A17B
Qwen3.5 397B A17B leads, 21.4 against 11.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only Qwen3.5 397B A17B has a Design Arena: websites result, 1190.
Directional only
Long documents
Listed context window
MiniMax M1
MiniMax M1 takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M1
MiniMax M1 $0.0015, Qwen3.5 397B A17B $0.0016 per turn.
List prices
At a glance
- Coding index
- MiniMax M1 not benchmarked, Qwen3.5 397B A17B not benchmarked.
- Widest category
- Reasoning, 19.4 points apart on average over 3 shared benchmarks.
- Widest single gap
- LMArena Text: Japanese: MiniMax M1 1217 against Qwen3.5 397B A17B 1429, 35.4 points apart on a 0 to 100 scale.
- Output price
- MiniMax M1 $2.20 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.1x apart.
- Context window
- MiniMax M1 takes 1M tokens, Qwen3.5 397B A17B 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 M1 | Bars | Qwen3.5 397B A17B | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 17 | ||
| All shared boards | 0 | 29 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1400 | Only Qwen3.5 397B A17B measured |
| SciCode | Not measured | 44.8% | Only Qwen3.5 397B A17B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 40.9% | Only Qwen3.5 397B A17B measured |
| ALE-Bench | Not measured | 621.9 | Only Qwen3.5 397B A17B measured |
| LMArena Text: coding | 1359 | 1464 | Qwen3.5 397B A17B |
| LMArena Text: software and IT | 1359 | 1463 | Qwen3.5 397B A17B |
| LMArena WebDev: React | Not measured | 1388 | Only Qwen3.5 397B A17B measured |
| LMArena WebDev: HTML | Not measured | 1410 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 35 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.7 | 21.4 | Qwen3.5 397B A17B |
| Epoch Capabilities Index | Not measured | 146.8 | Only Qwen3.5 397B A17B measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 95.6% | Only Qwen3.5 397B A17B measured |
| APEX-Agents | Not measured | 24.9% | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.3% | Only Qwen3.5 397B A17B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 29.0% | Only Qwen3.5 397B A17B measured |
| GPQA Diamond (Epoch AI run) | Not measured | 86.4% | Only Qwen3.5 397B A17B measured |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.5 397B A17B measured |
| LMArena Text: hard prompts | 1339 | 1448 | Qwen3.5 397B A17B |
| LMArena Text: expert | 1317 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: hard prompts in English | 1353 | 1450 | Qwen3.5 397B A17B |
| LMArena Vision: diagrams | Not measured | 1277 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: homework | Not measured | 1292 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 88.9% | Only Qwen3.5 397B A17B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 31.2% | Only Qwen3.5 397B A17B measured |
| LMArena Text: math | 1361 | 1453 | Qwen3.5 397B A17B |
| LMArena Text: mathematical work | 1363 | 1454 | Qwen3.5 397B A17B |
| MathArena | Not measured | 19.2% | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| LMArena Text: science | 1354 | 1457 | Qwen3.5 397B A17B |
| LMArena Text: medicine and healthcare | 1355 | 1455 | Qwen3.5 397B A17B |
| LMArena Text: legal and government | 1337 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: business and finance | 1319 | 1435 | Qwen3.5 397B A17B |
| Neither model has a result on the other 16 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1190 | Only Qwen3.5 397B A17B measured |
| Design Arena: UI components | Not measured | 1161 | Only Qwen3.5 397B A17B measured |
| Design Arena: game dev | Not measured | 1140 | Only Qwen3.5 397B A17B measured |
| Design Arena: data viz | Not measured | 1175 | Only Qwen3.5 397B A17B measured |
| Design Arena: 3D | Not measured | 1160 | Only Qwen3.5 397B A17B measured |
| Design Arena: all code categories | Not measured | 1179 | Only Qwen3.5 397B A17B measured |
| Design Arena: SVG | Not measured | 1139 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | Leader |
|---|---|---|---|
| IFBench | Not measured | 78.8% | Only Qwen3.5 397B A17B measured |
| Long context reasoning (AA-LCR) | Not measured | 77.3% | Only Qwen3.5 397B A17B measured |
| DTBench | Not measured | 87.5% | Only Qwen3.5 397B A17B measured |
| LMCA | Not measured | 37.9% | Only Qwen3.5 397B A17B measured |
| LMArena Text | 1343 | 1437 | Qwen3.5 397B A17B |
| LMArena Text: instruction following | 1312 | 1424 | Qwen3.5 397B A17B |
| LMArena Text: creative writing | 1297 | 1402 | Qwen3.5 397B A17B |
| LMArena Vision | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Text: English | 1363 | 1443 | Qwen3.5 397B A17B |
| LMArena Text: non-English | 1319 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Chinese | 1360 | 1498 | Qwen3.5 397B A17B |
| LMArena Text: German | 1350 | 1445 | Qwen3.5 397B A17B |
| LMArena Text: Japanese | 1217 | 1429 | Qwen3.5 397B A17B |
| LMArena Text: Korean | 1266 | 1384 | Qwen3.5 397B A17B |
| LMArena Text: French | 1370 | 1462 | Qwen3.5 397B A17B |
| LMArena Text: Spanish | 1353 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: Russian | 1329 | 1430 | Qwen3.5 397B A17B |
| LMArena Text: Polish | 1329 | 1447 | Qwen3.5 397B A17B |
| LMArena Text: multi-turn | 1335 | 1446 | Qwen3.5 397B A17B |
| LMArena Text: longer queries | 1326 | 1441 | Qwen3.5 397B A17B |
| LMArena Text: writing and language | 1311 | 1415 | Qwen3.5 397B A17B |
| LMArena Text: entertainment and media | 1303 | 1399 | Qwen3.5 397B A17B |
| LMArena Vision: English | Not measured | 1268 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: Chinese | Not measured | 1314 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: reading text | Not measured | 1271 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: humor | Not measured | 1262 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: captioning | Not measured | 1230 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: recognizing things | Not measured | 1265 | Only Qwen3.5 397B A17B measured |
| LMArena Vision: creative writing | Not measured | 1260 | Only Qwen3.5 397B A17B measured |
| Neither model has a result on the other 19 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M1 | Qwen3.5 397B A17B | 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
Qwen3.5 397B A17B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5 397B A17B 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 | Qwen3.5 397B A17B |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | No public weights listed | Open weights |
| Released | June 17, 2025 | February 16, 2026 |
| Context window | 1M | 262K |
| Input $/Mtok | $0.40 | $0.39 |
| Output $/Mtok | $2.20 | $2.34 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M1 better than Qwen3.5 397B A17B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M1 for output tokens 1.1x cheaper ($2.20 vs $2.34 per million) and a larger context window (1M against 262K tokens).
Which is cheaper, MiniMax M1 or Qwen3.5 397B A17B?
MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.
Which has the bigger context window, MiniMax M1 or Qwen3.5 397B A17B?
MiniMax M1, with 1M tokens against 262K.
How many benchmarks is the MiniMax M1 vs Qwen3.5 397B A17B comparison based on?
29 benchmarks have a result for both models as of October 22, 2026. MiniMax M1's coding index rests on 0 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.