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MiniMax M2.7 vs Qwen3.5-35B-A3B

MiniMax M2.7 leads Qwen3.5-35B-A3B on the Artificial Analysis Intelligence Index, 22.8 to 19.3, at about the same output price ($1.20 vs $1.30 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Qwen3.5-35B-A3B
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
35
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
5
vs boards won of 40 shared

MiniMax M2.7 or Qwen3.5-35B-A3B: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Qwen3.5-35B-A3B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-35B-A3B for a larger context window (262K against 205K tokens) and work measured by τ²-Bench Telecom or LMArena Text: medicine and healthcare, where it leads.

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
40
MiniMax M2.7 only
34
Qwen3.5-35B-A3B only
6
Like-for-like categories
7 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, Qwen3.5-35B-A3B not benchmarked.
Widest category
Coding, 14.3 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: React: MiniMax M2.7 1388 against Qwen3.5-35B-A3B 1238, 25.0 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Qwen3.5-35B-A3B $1.30 per million output tokens, 1.1x apart.
Context window
MiniMax M2.7 takes 205K tokens, Qwen3.5-35B-A3B 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.

Boards won, where both have a result
CategoryMiniMax M2.7BarsQwen3.5-35B-A3BTies
Coding70
Intelligence20
Agentic work01
Reasoning50
Math20
Knowledge31
General163
All shared boards355
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
LMArena WebDev13991254MiniMax M2.7
AA Coding Index52.6Not measuredOnly MiniMax M2.7 measured
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%Not measuredOnly MiniMax M2.7 measured
Code migration (Vals AI)8.7%Not measuredOnly MiniMax M2.7 measured
ProgramBench (Vals AI)0.0%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)48.7%Not measuredOnly MiniMax M2.7 measured
SciCode50.1%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)39.4%26.5%MiniMax M2.7
Terminal-Bench45.1%Not measuredOnly MiniMax M2.7 measured
WeirdML37.0%Not measuredOnly MiniMax M2.7 measured
ALE-Bench599.3221.8MiniMax M2.7
LMArena Text: coding14541410MiniMax M2.7
LMArena Text: software and IT14461415MiniMax M2.7
LMArena WebDev: React13881238MiniMax M2.7
LMArena WebDev: HTML14011301MiniMax M2.7
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
AA Intelligence Index22.819.3MiniMax M2.7
Epoch Capabilities Index145.8142.5MiniMax M2.7
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
AA Agentic Index15.3Not measuredOnly MiniMax M2.7 measured
Finance Agent (Vals AI)27.9%Not measuredOnly MiniMax M2.7 measured
Tax Agent Bench (Vals AI)6.9%Not measuredOnly MiniMax M2.7 measured
Legal Research Bench (Vals AI)10.6%Not measuredOnly MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)28.4%Not measuredOnly MiniMax M2.7 measured
τ²-Bench Telecom84.8%89.2%Qwen3.5-35B-A3B
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
GPQA Diamond86.6%Not measuredOnly MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)87.4%84.5%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)29.6%21.0%MiniMax M2.7
GPQA Diamond (Epoch AI run)Not measured83.5%Only Qwen3.5-35B-A3B measured
LMArena Text: hard prompts14221400MiniMax M2.7
LMArena Text: expert14431408MiniMax M2.7
LMArena Text: hard prompts in English14411411MiniMax M2.7
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
AIME91.0%Not measuredOnly MiniMax M2.7 measured
OTIS Mock AIMENot measured70.0%Only Qwen3.5-35B-A3B measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math14211404MiniMax M2.7
LMArena Text: mathematical work14371410MiniMax M2.7
MathArenaNot measured14.7%Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
Knowledge benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
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
MedCode (Vals AI)34.4%Not measuredOnly MiniMax M2.7 measured
LMArena Text: science14161413MiniMax M2.7
LMArena Text: medicine and healthcare14091421Qwen3.5-35B-A3B
LMArena Text: legal and government14031399MiniMax M2.7
LMArena Text: business and finance14071394MiniMax M2.7
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
Web design benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
Design Arena: websites1242Not measuredOnly MiniMax M2.7 measured
Design Arena: UI components1207Not measuredOnly MiniMax M2.7 measured
Design Arena: game dev1209Not measuredOnly MiniMax M2.7 measured
Design Arena: data viz1233Not measuredOnly MiniMax M2.7 measured
Design Arena: 3D1194Not measuredOnly MiniMax M2.7 measured
Design Arena: all code categories1233Not measuredOnly MiniMax M2.7 measured
Design Arena: SVG1137Not measuredOnly MiniMax M2.7 measured
Design Arena: ASCII art1136Not measuredOnly 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 index163
General benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
MedScribe (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
IFBench75.7%72.5%MiniMax M2.7
Long context reasoning (AA-LCR)78.3%72.0%MiniMax M2.7
DTBenchNot measured80.0%Only Qwen3.5-35B-A3B measured
LMCANot measured29.5%Only Qwen3.5-35B-A3B measured
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text14051395MiniMax M2.7
LMArena Text: instruction following14051379MiniMax M2.7
LMArena Text: creative writing13541347MiniMax M2.7
LMArena Text: English14261407MiniMax M2.7
LMArena Text: non-English13821378MiniMax M2.7
LMArena Text: Chinese14421457Qwen3.5-35B-A3B
LMArena Text: German13981367MiniMax M2.7
LMArena Text: Japanese12601326Qwen3.5-35B-A3B
LMArena Text: Korean13141355Qwen3.5-35B-A3B
LMArena Text: French14241412MiniMax M2.7
LMArena Text: Spanish14021390MiniMax M2.7
LMArena Text: Russian13831376MiniMax M2.7
LMArena Text: Polish13871385MiniMax M2.7
LMArena Text: multi-turn14121390MiniMax M2.7
LMArena Text: longer queries14181389MiniMax M2.7
LMArena Text: writing and language13761365MiniMax M2.7
LMArena Text: entertainment and media13601347MiniMax M2.7
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
Image generation benchmarks for MiniMax M2.7 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.7Qwen3.5-35B-A3BLeader
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
Qwen3.5-35B-A3B$0.0008Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Qwen3.5-35B-A3B$0.012Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Qwen3.5-35B-A3B$0.045Fits in one request

Qwen3.5-35B-A3B 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 Qwen3.5-35B-A3B
SpecificationMiniMax M2.7Qwen3.5-35B-A3B
MakerMiniMaxQwen
WeightsOpen weightsOpen weights
ReleasedMarch 18, 2026February 25, 2026
Context window205K262K
Input $/Mtok$0.30$0.1625
Output $/Mtok$1.20$1.30
Coding index36.2Not benchmarked
Independent measurements behind it31
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than Qwen3.5-35B-A3B for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Qwen3.5-35B-A3B has none, so the two cannot be ranked on coding. Pick Qwen3.5-35B-A3B for a larger context window (262K against 205K tokens) and work measured by τ²-Bench Telecom or LMArena Text: medicine and healthcare, where it leads.

Which is cheaper, MiniMax M2.7 or Qwen3.5-35B-A3B?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B, with 262K tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs Qwen3.5-35B-A3B comparison based on?

40 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.7's coding index rests on 3 independent benchmarks and Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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