MiniMax M2.7 vs Qwen2.5 Coder 32B Instruct
Updated October 21, 2026. 26 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen2.5 Coder 32B Instruct for coding: it scores 30.5 on the Vibe Coding Index against 28.4 for MiniMax M2.7.
Pick MiniMax M2.7 when the context window is larger, 205K against 33K tokens, or when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.
- Shared results
- 26
- MiniMax M2.7 only
- 48
- Qwen2.5 Coder 32B Instruct only
- 9
- 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
Qwen2.5 Coder 32B Instruct
Qwen2.5 Coder 32B Instruct scores 30.5 against 28.4.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
MiniMax M2.7
MiniMax M2.7 leads, 22.8 against 6.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only MiniMax M2.7 has a AA Agentic Index result, 15.3.
Directional only
Reasoning
GPQA Diamond
No call
Only MiniMax M2.7 has a GPQA Diamond result, 86.6%.
Directional only
Math
AIME
No call
Only MiniMax M2.7 has a AIME result, 91.0%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.7 has a MMLU Pro result, 80.4%.
Directional only
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
MiniMax M2.7
MiniMax M2.7 takes 205K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.7
MiniMax M2.7 $0.0009, Qwen2.5 Coder 32B Instruct $0.0012 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.7 has the number, $0.64.
Directional only
At a glance
- Coding index
- MiniMax M2.7 28.4 from 1 benchmark, Qwen2.5 Coder 32B Instruct 30.5 from 2 benchmarks.
- Widest category
- Reasoning, 33.2 points apart on average over 5 shared benchmarks.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): MiniMax M2.7 87.4% against Qwen2.5 Coder 32B Instruct 41.7%, 45.7 points apart on a 0 to 100 scale.
- Output price
- MiniMax M2.7 $1.20 against Qwen2.5 Coder 32B Instruct $1.00 per million output tokens, 1.2x apart.
- Context window
- MiniMax M2.7 takes 205K tokens, Qwen2.5 Coder 32B Instruct 33K.
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 | Qwen2.5 Coder 32B Instruct | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 5 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 11 | 0 | ||
| All shared boards | 26 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index20
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 16.4% | Only Qwen2.5 Coder 32B Instruct measured |
| SWE-bench Verified | Not measured | 47.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena WebDev | 1399 | Not measured | Only MiniMax M2.7 measured |
| AA Coding Index | 52.6 | Not measured | Only MiniMax M2.7 measured |
| LiveCodeBench (Vals AI) | 79.9% | Not measured | Only MiniMax M2.7 measured |
| SWE-bench Verified (Vals AI) | 73.8% | Not measured | Only MiniMax M2.7 measured |
| 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 29.5% | Only Qwen2.5 Coder 32B Instruct 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 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: coding | 1454 | 1276 | MiniMax M2.7 |
| LMArena Text: software and IT | 1446 | 1261 | MiniMax M2.7 |
| LMArena WebDev: React | 1388 | Not measured | Only MiniMax M2.7 measured |
| LMArena WebDev: HTML | 1401 | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.8 | 6.7 | MiniMax M2.7 |
| Epoch Capabilities Index | 145.8 | 119.5 | MiniMax M2.7 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | 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 index50
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 86.6% | Not measured | Only MiniMax M2.7 measured |
| GPQA Diamond (Artificial Analysis run) | 87.4% | 41.7% | MiniMax M2.7 |
| Humanity's Last Exam (Artificial Analysis run) | 29.6% | 3.5% | MiniMax M2.7 |
| LMArena Text: hard prompts | 1422 | 1251 | MiniMax M2.7 |
| LMArena Text: expert | 1443 | 1221 | MiniMax M2.7 |
| LMArena Text: hard prompts in English | 1441 | 1269 | MiniMax M2.7 |
| Neither model has a result on the other 15 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| AIME | 91.0% | Not measured | Only MiniMax M2.7 measured |
| ProofBench | 3.0% | Not measured | Only MiniMax M2.7 measured |
| GSM8K | Not measured | 93.0% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: math | 1421 | 1251 | MiniMax M2.7 |
| LMArena Text: mathematical work | 1437 | 1243 | MiniMax M2.7 |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 80.4% | Not measured | Only MiniMax M2.7 measured |
| LegalBench (Vals AI) | 84.0% | Not measured | Only MiniMax M2.7 measured |
| CaseLaw (Vals AI) | 60.9% | Not measured | Only MiniMax M2.7 measured |
| CorpFin (Vals AI) | 61.2% | Not measured | Only MiniMax M2.7 measured |
| TaxEval (Vals AI) | 66.6% | Not measured | Only MiniMax M2.7 measured |
| MedCode (Vals AI) | 34.4% | Not measured | Only MiniMax M2.7 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 63.5% | Only Qwen2.5 Coder 32B Instruct measured |
| MMLU | Not measured | 79.1% | Only Qwen2.5 Coder 32B Instruct measured |
| AI2 Reasoning Challenge | Not measured | 70.5% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text: science | 1416 | 1221 | MiniMax M2.7 |
| LMArena Text: medicine and healthcare | 1409 | 1187 | MiniMax M2.7 |
| LMArena Text: legal and government | 1403 | 1257 | MiniMax M2.7 |
| LMArena Text: business and finance | 1407 | 1224 | MiniMax M2.7 |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | 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 index110
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 79.9% | Not measured | Only MiniMax M2.7 measured |
| IFBench | 75.7% | Not measured | Only MiniMax M2.7 measured |
| Long context reasoning (AA-LCR) | 78.3% | Not measured | Only MiniMax M2.7 measured |
| ExploitBench | 13.3% | Not measured | Only MiniMax M2.7 measured |
| HellaSwag | Not measured | 83.0% | Only Qwen2.5 Coder 32B Instruct measured |
| WinoGrande | Not measured | 80.8% | Only Qwen2.5 Coder 32B Instruct measured |
| LMArena Text | 1405 | 1230 | MiniMax M2.7 |
| LMArena Text: instruction following | 1405 | 1223 | MiniMax M2.7 |
| LMArena Text: creative writing | 1354 | 1174 | MiniMax M2.7 |
| LMArena Text: English | 1426 | 1248 | MiniMax M2.7 |
| LMArena Text: non-English | 1382 | 1205 | MiniMax M2.7 |
| LMArena Text: Chinese | 1442 | 1222 | MiniMax M2.7 |
| LMArena Text: German | 1398 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Japanese | 1260 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Korean | 1314 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: French | 1424 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Spanish | 1402 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Russian | 1383 | 1228 | MiniMax M2.7 |
| LMArena Text: Polish | 1387 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: multi-turn | 1412 | 1222 | MiniMax M2.7 |
| LMArena Text: longer queries | 1418 | 1251 | MiniMax M2.7 |
| LMArena Text: writing and language | 1376 | 1191 | MiniMax M2.7 |
| LMArena Text: entertainment and media | 1360 | 1150 | MiniMax M2.7 |
| Neither model has a result on the other 23 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | MiniMax M2.7 | Qwen2.5 Coder 32B Instruct | 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 M2.7 costs less
Repository review
50K input + 3K output tokens
MiniMax M2.7 costs less
Agent loop
200K input + 10K output tokens
MiniMax M2.7 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 | Qwen2.5 Coder 32B Instruct |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | Open weights | Open weights |
| Released | March 18, 2026 | November 11, 2024 |
| Context window | 205K | 33K |
| Input $/Mtok | $0.30 | $0.66 |
| Output $/Mtok | $1.20 | $1.00 |
| Coding index | 28.4 | 30.5 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $0.64 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.7 better than Qwen2.5 Coder 32B Instruct for coding?
Pick Qwen2.5 Coder 32B Instruct for coding: it scores 30.5 on the Vibe Coding Index against 28.4 for MiniMax M2.7. Pick MiniMax M2.7 when the context window is larger, 205K against 33K tokens, or when what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, MiniMax M2.7 or Qwen2.5 Coder 32B Instruct?
MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen2.5 Coder 32B Instruct costs $0.66 and $1.00. Cost per solved task is known for MiniMax M2.7 only.
Which has the bigger context window, MiniMax M2.7 or Qwen2.5 Coder 32B Instruct?
MiniMax M2.7, with 205K tokens against 33K.
How many benchmarks is the MiniMax M2.7 vs Qwen2.5 Coder 32B Instruct comparison based on?
26 benchmarks have a result for both models as of October 21, 2026. MiniMax M2.7's coding index rests on 1 independent benchmark and Qwen2.5 Coder 32B Instruct's on 2. Where only one model has a result, the page says so instead of naming a winner.