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MiniMax M2.7 vs Qwen3.7 Plus

MiniMax M2.7 leads Qwen3.7 Plus on coding, 36.2 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; 54 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Qwen3.7 Plus
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
2
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
52
vs boards won of 54 shared

MiniMax M2.7 or Qwen3.7 Plus: which to pick

Pick MiniMax M2.7 for coding: it scores 36.2 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus.

Pick Qwen3.7 Plus for a larger context window (1M against 205K tokens) and work measured by AA Coding Index or Vibe Code Bench (Vals AI), where it leads.

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
54
MiniMax M2.7 only
20
Qwen3.7 Plus only
21
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.

At a glance

Coding index
MiniMax M2.7 36.2 from 3 benchmarks, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
General, 10.0 points apart on average over 19 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): MiniMax M2.7 11.9% against Qwen3.7 Plus 46.4%, 34.5 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Qwen3.7 Plus $1.28 per million output tokens, 1.1x apart.
Context window
MiniMax M2.7 takes 205K 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.

Boards won, where both have a result
CategoryMiniMax M2.7BarsQwen3.7 PlusTies
Coding17
Intelligence02
Agentic work06
Reasoning05
Math02
Knowledge04
Web design08
General118
All shared boards252
CodingLike-for-likeSix of these boards feed the Vibe Coding Index17
Coding benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
LMArena WebDev1399Not measuredOnly MiniMax M2.7 measured
AA Coding Index52.655.9Qwen3.7 Plus
LiveCodeBench (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
SWE-bench Verified (Vals AI)73.8%Not measuredOnly MiniMax M2.7 measured
Vibe Code Bench (Vals AI)11.9%46.4%Qwen3.7 Plus
Code migration (Vals AI)8.7%12.9%Qwen3.7 Plus
ProgramBench (Vals AI)0.0%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)48.7%52.8%Qwen3.7 Plus
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
SciCode50.1%46.1%MiniMax M2.7
Terminal-Bench Hard (Artificial Analysis run)39.4%47.0%Qwen3.7 Plus
Terminal-Bench45.1%Not measuredOnly MiniMax M2.7 measured
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
WeirdML37.0%Not measuredOnly MiniMax M2.7 measured
ALE-Bench599.3Not measuredOnly MiniMax M2.7 measured
LMArena Text: coding14541473Qwen3.7 Plus
LMArena Text: software and IT14461473Qwen3.7 Plus
LMArena WebDev: React1388Not measuredOnly MiniMax M2.7 measured
LMArena WebDev: HTML1401Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
AA Intelligence Index22.825.2Qwen3.7 Plus
Epoch Capabilities Index145.8147.0Qwen3.7 Plus
Agentic workLike-for-likePublic boards, shown as published, kept out of the index06
Agentic work benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
AA Agentic Index15.317.5Qwen3.7 Plus
Finance Agent (Vals AI)27.9%38.2%Qwen3.7 Plus
Tax Agent Bench (Vals AI)6.9%10.5%Qwen3.7 Plus
Legal Research Bench (Vals AI)10.6%16.4%Qwen3.7 Plus
Excel Modeling Benchmark (Vals AI)28.4%49.3%Qwen3.7 Plus
τ²-Bench Telecom84.8%93.0%Qwen3.7 Plus
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
GPQA Diamond86.6%Not measuredOnly MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)87.4%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)29.6%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)Not measured87.9%Only Qwen3.7 Plus measured
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts14221460Qwen3.7 Plus
LMArena Text: expert14431466Qwen3.7 Plus
LMArena Text: hard prompts in English14411460Qwen3.7 Plus
LMArena Vision: diagramsNot measured1292Only Qwen3.7 Plus measured
LMArena Vision: homeworkNot measured1295Only Qwen3.7 Plus measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
AIME91.0%Not measuredOnly MiniMax M2.7 measured
OTIS Mock AIMENot measured93.3%Only Qwen3.7 Plus measured
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math14211467Qwen3.7 Plus
LMArena Text: mathematical work14371470Qwen3.7 Plus
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
MMLU Pro80.4%Not measuredOnly MiniMax M2.7 measured
LegalBench (Vals AI)84.0%Not measuredOnly MiniMax M2.7 measured
CaseLaw (Vals AI)60.9%Not measuredOnly MiniMax M2.7 measured
CorpFin (Vals AI)61.2%Not measuredOnly MiniMax M2.7 measured
TaxEval (Vals AI)66.6%Not measuredOnly MiniMax M2.7 measured
MortgageTax (Vals AI)Not measured66.2%Only Qwen3.7 Plus measured
MedCode (Vals AI)34.4%Not measuredOnly MiniMax M2.7 measured
LMArena Text: science14161464Qwen3.7 Plus
LMArena Text: medicine and healthcare14091464Qwen3.7 Plus
LMArena Text: legal and government14031451Qwen3.7 Plus
LMArena Text: business and finance14071435Qwen3.7 Plus
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
Design Arena: websites12431269Qwen3.7 Plus
Design Arena: UI components12101258Qwen3.7 Plus
Design Arena: game dev12091261Qwen3.7 Plus
Design Arena: data viz12331276Qwen3.7 Plus
Design Arena: 3D11951238Qwen3.7 Plus
Design Arena: all code categories12331269Qwen3.7 Plus
Design Arena: SVG11371208Qwen3.7 Plus
Design Arena: ASCII art11361143Qwen3.7 Plus
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index118
General benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
MedScribe (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBench75.7%78.0%Qwen3.7 Plus
Long context reasoning (AA-LCR)78.3%73.0%MiniMax M2.7
DTBenchNot measured84.0%Only Qwen3.7 Plus measured
LMCANot measured37.6%Only Qwen3.7 Plus measured
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text14051454Qwen3.7 Plus
LMArena Text: instruction following14051439Qwen3.7 Plus
LMArena Text: creative writing13541438Qwen3.7 Plus
LMArena VisionNot measured1278Only Qwen3.7 Plus measured
LMArena Text: English14261458Qwen3.7 Plus
LMArena Text: non-English13821445Qwen3.7 Plus
LMArena Text: Chinese14421509Qwen3.7 Plus
LMArena Text: German13981471Qwen3.7 Plus
LMArena Text: Japanese12601412Qwen3.7 Plus
LMArena Text: Korean13141413Qwen3.7 Plus
LMArena Text: French14241472Qwen3.7 Plus
LMArena Text: Spanish14021457Qwen3.7 Plus
LMArena Text: Russian13831457Qwen3.7 Plus
LMArena Text: Polish13871449Qwen3.7 Plus
LMArena Text: multi-turn14121459Qwen3.7 Plus
LMArena Text: longer queries14181454Qwen3.7 Plus
LMArena Text: writing and language13761437Qwen3.7 Plus
LMArena Text: entertainment and media13601422Qwen3.7 Plus
LMArena Vision: EnglishNot measured1280Only Qwen3.7 Plus measured
LMArena Vision: ChineseNot measured1332Only Qwen3.7 Plus measured
LMArena Vision: reading textNot measured1288Only Qwen3.7 Plus measured
LMArena Vision: humorNot measured1261Only Qwen3.7 Plus measured
LMArena Vision: creative writingNot measured1258Only Qwen3.7 Plus measured
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for MiniMax M2.7 and Qwen3.7 Plus
BenchmarkMiniMax M2.7Qwen3.7 PlusLeader
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$0.0009Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Qwen3.7 Plus$0.020Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Qwen3.7 Plus$0.077Fits in one request

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.

Specifications of MiniMax M2.7 and Qwen3.7 Plus
SpecificationMiniMax M2.7Qwen3.7 Plus
MakerMiniMaxQwen
WeightsOpen weightsNo public weights listed
ReleasedMarch 18, 2026June 3, 2026
Context window205K1M
Input $/Mtok$0.30$0.32
Output $/Mtok$1.20$1.28
Coding index36.233.2
Independent measurements behind it32
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than Qwen3.7 Plus for coding?

Pick MiniMax M2.7 for coding: it scores 36.2 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus. Pick Qwen3.7 Plus for a larger context window (1M against 205K tokens) and work measured by AA Coding Index or Vibe Code Bench (Vals AI), where it leads.

Which is cheaper, MiniMax M2.7 or Qwen3.7 Plus?

MiniMax M2.7 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 M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Qwen3.7 Plus?

Qwen3.7 Plus, with 1M tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs Qwen3.7 Plus comparison based on?

54 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.7's coding index rests on 3 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.

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