MiniMax M2.7 vs Qwen3.5-Flash
Updated October 21, 2026. 44 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick MiniMax M2.7 for coding: it scores 28.4 on the Vibe Coding Index against 6.2 for Qwen3.5-Flash.
Pick Qwen3.5-Flash when output tokens cost 4.6x less, or when a solved task costs $0.40 against $0.64.
- Shared results
- 44
- MiniMax M2.7 only
- 30
- Qwen3.5-Flash only
- 11
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
MiniMax M2.7
MiniMax M2.7 scores 28.4 against 6.2.
One benchmark behind each score
Intelligence
AA Intelligence Index
No call
Only MiniMax M2.7 has a AA Intelligence Index result, 22.8.
Directional only
Agentic work
AA Agentic Index
No call
Only MiniMax M2.7 has a AA Agentic Index result, 15.3.
Directional only
Reasoning
GPQA Diamond
MiniMax M2.7
MiniMax M2.7 leads, 86.6% against 82.8%.
Same board, both measured
Math
AIME
Qwen3.5-Flash
Qwen3.5-Flash leads, 92.5% against 91.0%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.5-Flash
Qwen3.5-Flash leads, 84.1% against 80.4%.
Same board, both measured
Web design
Design Arena: websites
No call
Only MiniMax M2.7 has a Design Arena: websites result, 1243.
Directional only
Long documents
Listed context window
Qwen3.5-Flash
Qwen3.5-Flash takes 1M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.5-Flash
MiniMax M2.7 $0.0009, Qwen3.5-Flash $0.0002 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Qwen3.5-Flash
MiniMax M2.7 $0.64, Qwen3.5-Flash $0.40.
Published attempt cost and pass rate
At a glance
- Coding index
- MiniMax M2.7 28.4 from 1 benchmark, Qwen3.5-Flash 6.2 from 1 benchmark.
- Widest category
- Coding, 12.8 points apart on average over 8 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: MiniMax M2.7 1388 against Qwen3.5-Flash 1229, 26.4 points apart on a 0 to 100 scale.
- Output price
- MiniMax M2.7 $1.20 against Qwen3.5-Flash $0.26 per million output tokens, 4.6x apart.
- Context window
- MiniMax M2.7 takes 205K tokens, Qwen3.5-Flash 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 M2.7 | Bars | Qwen3.5-Flash | Ties |
|---|---|---|---|---|
| Coding | 7 | 1 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 2 | 1 | ||
| Knowledge | 6 | 4 | ||
| General | 14 | 4 | ||
| All shared boards | 34 | 10 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index71
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| LMArena WebDev | 1399 | 1244 | MiniMax M2.7 |
| AA Coding Index | 52.6 | Not measured | Only MiniMax M2.7 measured |
| LiveCodeBench (Vals AI) | 79.9% | 83.3% | Qwen3.5-Flash |
| SWE-bench Verified (Vals AI) | 73.8% | 64.4% | MiniMax M2.7 |
| Vibe Code Bench (Vals AI) | 11.9% | Not measured | Only MiniMax M2.7 measured |
| Code migration (Vals AI) | 8.7% | Not measured | Only MiniMax M2.7 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only MiniMax M2.7 measured |
| Terminal-Bench 2.1 (Vals AI) | 48.7% | Not measured | Only MiniMax M2.7 measured |
| SciCode | 50.1% | Not measured | Only MiniMax M2.7 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 39.4% | Not measured | Only MiniMax M2.7 measured |
| Terminal-Bench | 45.1% | Not measured | Only MiniMax M2.7 measured |
| WeirdML | 37.0% | Not measured | Only MiniMax M2.7 measured |
| ALE-Bench | 599.3 | 265.9 | MiniMax M2.7 |
| LMArena Text: coding | 1454 | 1412 | MiniMax M2.7 |
| LMArena Text: software and IT | 1446 | 1416 | MiniMax M2.7 |
| LMArena WebDev: React | 1388 | 1229 | MiniMax M2.7 |
| LMArena WebDev: HTML | 1401 | 1291 | MiniMax M2.7 |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.8 | Not measured | Only MiniMax M2.7 measured |
| Epoch Capabilities Index | 145.8 | 143.5 | MiniMax M2.7 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AA Agentic Index | 15.3 | Not measured | Only MiniMax M2.7 measured |
| Finance Agent (Vals AI) | 27.9% | Not measured | Only MiniMax M2.7 measured |
| Tax Agent Bench (Vals AI) | 6.9% | Not measured | Only MiniMax M2.7 measured |
| Legal Research Bench (Vals AI) | 10.6% | Not measured | Only MiniMax M2.7 measured |
| Excel Modeling Benchmark (Vals AI) | 28.4% | Not measured | Only MiniMax M2.7 measured |
| τ²-Bench Telecom | 84.8% | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 33 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 86.6% | 82.8% | MiniMax M2.7 |
| MMMU Pro (Vals AI) | Not measured | 81.9% | Only Qwen3.5-Flash measured |
| GPQA Diamond (Artificial Analysis run) | 87.4% | Not measured | Only MiniMax M2.7 measured |
| Humanity's Last Exam (Artificial Analysis run) | 29.6% | Not measured | Only MiniMax M2.7 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 82.3% | Only Qwen3.5-Flash measured |
| Chess puzzles | Not measured | 14.0% | Only Qwen3.5-Flash measured |
| Mystery game puzzles | Not measured | 20.0% | Only Qwen3.5-Flash measured |
| LMArena Text: hard prompts | 1422 | 1403 | MiniMax M2.7 |
| LMArena Text: expert | 1443 | 1407 | MiniMax M2.7 |
| LMArena Text: hard prompts in English | 1441 | 1409 | MiniMax M2.7 |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| AIME | 91.0% | 92.5% | Qwen3.5-Flash |
| OTIS Mock AIME | Not measured | 84.4% | Only Qwen3.5-Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 18.2% | Only Qwen3.5-Flash measured |
| ProofBench | 3.0% | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: math | 1421 | 1407 | MiniMax M2.7 |
| LMArena Text: mathematical work | 1437 | 1413 | MiniMax M2.7 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index64
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| MMLU Pro | 80.4% | 84.1% | Qwen3.5-Flash |
| LegalBench (Vals AI) | 84.0% | 84.3% | Qwen3.5-Flash |
| CaseLaw (Vals AI) | 60.9% | 56.0% | MiniMax M2.7 |
| CorpFin (Vals AI) | 61.2% | 63.6% | Qwen3.5-Flash |
| TaxEval (Vals AI) | 66.6% | 72.2% | Qwen3.5-Flash |
| MortgageTax (Vals AI) | Not measured | 67.4% | Only Qwen3.5-Flash measured |
| MedCode (Vals AI) | 34.4% | 33.0% | MiniMax M2.7 |
| SimpleQA Verified | Not measured | 20.3% | Only Qwen3.5-Flash measured |
| LMArena Text: science | 1416 | 1415 | MiniMax M2.7 |
| LMArena Text: medicine and healthcare | 1409 | 1407 | MiniMax M2.7 |
| LMArena Text: legal and government | 1403 | 1398 | MiniMax M2.7 |
| LMArena Text: business and finance | 1407 | 1394 | MiniMax M2.7 |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1243 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: UI components | 1210 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: game dev | 1210 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: data viz | 1233 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: 3D | 1195 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: all code categories | 1233 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: SVG | 1136 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: ASCII art | 1136 | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index144
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 42.5% | Only Qwen3.5-Flash measured |
| MedScribe (Vals AI) | 79.9% | 70.6% | MiniMax M2.7 |
| IFBench | 75.7% | Not measured | Only MiniMax M2.7 measured |
| Long context reasoning (AA-LCR) | 78.3% | Not measured | Only MiniMax M2.7 measured |
| DTBench | Not measured | 82.9% | Only Qwen3.5-Flash measured |
| LMCA | Not measured | 29.1% | Only Qwen3.5-Flash measured |
| ExploitBench | 13.3% | Not measured | Only MiniMax M2.7 measured |
| LMArena Text | 1405 | 1397 | MiniMax M2.7 |
| LMArena Text: instruction following | 1405 | 1374 | MiniMax M2.7 |
| LMArena Text: creative writing | 1354 | 1343 | MiniMax M2.7 |
| LMArena Text: English | 1426 | 1404 | MiniMax M2.7 |
| LMArena Text: non-English | 1382 | 1385 | Qwen3.5-Flash |
| LMArena Text: Chinese | 1442 | 1445 | Qwen3.5-Flash |
| LMArena Text: German | 1398 | 1390 | MiniMax M2.7 |
| LMArena Text: Japanese | 1260 | 1369 | Qwen3.5-Flash |
| LMArena Text: Korean | 1314 | 1344 | Qwen3.5-Flash |
| LMArena Text: French | 1424 | 1413 | MiniMax M2.7 |
| LMArena Text: Spanish | 1402 | 1400 | MiniMax M2.7 |
| LMArena Text: Russian | 1383 | 1380 | MiniMax M2.7 |
| LMArena Text: Polish | 1387 | 1376 | MiniMax M2.7 |
| LMArena Text: multi-turn | 1412 | 1393 | MiniMax M2.7 |
| LMArena Text: longer queries | 1418 | 1392 | MiniMax M2.7 |
| LMArena Text: writing and language | 1376 | 1369 | MiniMax M2.7 |
| LMArena Text: entertainment and media | 1360 | 1347 | MiniMax M2.7 |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M2.7 | Qwen3.5-Flash | 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
Qwen3.5-Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.5-Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-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 M2.7 | Qwen3.5-Flash |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | Open weights | No public weights listed |
| Released | March 18, 2026 | February 25, 2026 |
| Context window | 205K | 1M |
| Input $/Mtok | $0.30 | $0.065 |
| Output $/Mtok | $1.20 | $0.26 |
| Coding index | 28.4 | 6.2 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.64 | $0.40 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.7 better than Qwen3.5-Flash for coding?
Pick MiniMax M2.7 for coding: it scores 28.4 on the Vibe Coding Index against 6.2 for Qwen3.5-Flash. Pick Qwen3.5-Flash when output tokens cost 4.6x less, or when a solved task costs $0.40 against $0.64.
Which is cheaper, MiniMax M2.7 or Qwen3.5-Flash?
MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Per solved SWE-bench Verified task, MiniMax M2.7 costs $0.64 and Qwen3.5-Flash $0.40.
Which has the bigger context window, MiniMax M2.7 or Qwen3.5-Flash?
Qwen3.5-Flash, with 1M tokens against 205K.
How many benchmarks is the MiniMax M2.7 vs Qwen3.5-Flash comparison based on?
44 benchmarks have a result for both models as of October 21, 2026. MiniMax M2.7's coding index rests on 1 independent benchmark and Qwen3.5-Flash's on 1. Where only one model has a result, the page says so instead of naming a winner.