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MiniMax M2.1 vs Qwen3.5-35B-A3B

MiniMax M2.1 leads Qwen3.5-35B-A3B on the Artificial Analysis Intelligence Index, 20.9 to 19.3, at about the same output price ($1.20 vs $1.30 per million). Updated October 23, 2026; 8 benchmarks have a result for both.

MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
4
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
4
vs boards won of 8 shared

MiniMax M2.1 or Qwen3.5-35B-A3B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick MiniMax M2.1 for output tokens 1.1x cheaper ($1.20 vs $1.30 per million) and work measured by τ²-Bench Telecom or GPQA Diamond (Artificial Analysis run), where it leads.

Shared results
8
MiniMax M2.1 only
26
Qwen3.5-35B-A3B only
38
Like-for-like categories
5 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 M2.1 not benchmarked, Qwen3.5-35B-A3B not benchmarked.
Widest category
Coding, 7.8 points apart on average over 2 shared benchmarks.
Widest single gap
ALE-Bench: MiniMax M2.1 623.8 against Qwen3.5-35B-A3B 221.8, 13.4 points apart on a 0 to 100 scale.
Output price
MiniMax M2.1 $1.20 against Qwen3.5-35B-A3B $1.30 per million output tokens, 1.1x apart.
Context window
MiniMax M2.1 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 M2.1BarsQwen3.5-35B-A3BTies
Coding20
Intelligence10
Agentic work01
Reasoning11
General02
All shared boards44
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-A3BLeader
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
LiveCodeBench (Vals AI)81.8%Not measuredOnly MiniMax M2.1 measured
SWE-bench Verified (Vals AI)74.8%Not measuredOnly MiniMax M2.1 measured
LiveCodeBench (Artificial Analysis run)81.0%Not measuredOnly MiniMax M2.1 measured
Terminal-Bench Hard (Artificial Analysis run)28.8%26.5%MiniMax M2.1
Terminal-Bench36.6%Not measuredOnly MiniMax M2.1 measured
ALE-Bench623.8221.8MiniMax M2.1
LMArena Text: codingNot measured1410Only Qwen3.5-35B-A3B measured
LMArena Text: software and ITNot measured1415Only Qwen3.5-35B-A3B measured
LMArena WebDev: ReactNot measured1238Only Qwen3.5-35B-A3B measured
LMArena WebDev: HTMLNot measured1301Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-A3BLeader
AA Intelligence Index20.919.3MiniMax M2.1
Epoch Capabilities IndexNot measured142.5Only Qwen3.5-35B-A3B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-A3BLeader
τ²-Bench Telecom85.4%89.2%Qwen3.5-35B-A3B
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
Reasoning benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-A3BLeader
GPQA Diamond78.5%Not measuredOnly MiniMax M2.1 measured
GPQA Diamond (Artificial Analysis run)83.0%84.5%Qwen3.5-35B-A3B
Humanity's Last Exam (Artificial Analysis run)23.2%21.0%MiniMax M2.1
GPQA Diamond (Epoch AI run)Not measured83.5%Only Qwen3.5-35B-A3B measured
LMArena Text: hard promptsNot measured1400Only Qwen3.5-35B-A3B measured
LMArena Text: expertNot measured1407Only Qwen3.5-35B-A3B measured
LMArena Text: hard prompts in EnglishNot measured1411Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Math benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-A3BLeader
AIME77.9%Not measuredOnly MiniMax M2.1 measured
MATH 500 (Vals AI)89.0%Not measuredOnly MiniMax M2.1 measured
MGSM (Vals AI)87.8%Not measuredOnly MiniMax M2.1 measured
AA Math Index82.7Not measuredOnly MiniMax M2.1 measured
AIME 2025 (Artificial Analysis run)82.7%Not measuredOnly MiniMax M2.1 measured
OTIS Mock AIMENot measured70.0%Only Qwen3.5-35B-A3B measured
LMArena Text: mathNot measured1404Only Qwen3.5-35B-A3B measured
LMArena Text: mathematical workNot measured1410Only Qwen3.5-35B-A3B measured
MathArenaNot measured14.7%Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 5 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Knowledge benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-A3BLeader
MMLU Pro87.0%Not measuredOnly MiniMax M2.1 measured
LegalBench (Vals AI)75.5%Not measuredOnly MiniMax M2.1 measured
CaseLaw (Vals AI)55.8%Not measuredOnly MiniMax M2.1 measured
CorpFin (Vals AI)58.9%Not measuredOnly MiniMax M2.1 measured
TaxEval (Vals AI)66.3%Not measuredOnly MiniMax M2.1 measured
MedQA (Vals AI)91.2%Not measuredOnly MiniMax M2.1 measured
MedCode (Vals AI)34.1%Not measuredOnly MiniMax M2.1 measured
MMLU Pro (Artificial Analysis run)87.5%Not measuredOnly MiniMax M2.1 measured
LMArena Text: scienceNot measured1413Only Qwen3.5-35B-A3B measured
LMArena Text: medicine and healthcareNot measured1421Only Qwen3.5-35B-A3B measured
LMArena Text: legal and governmentNot measured1398Only Qwen3.5-35B-A3B measured
LMArena Text: business and financeNot measured1394Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-A3BLeader
Design Arena: websites1201Not measuredOnly MiniMax M2.1 measured
Design Arena: UI components1220Not measuredOnly MiniMax M2.1 measured
Design Arena: game dev1134Not measuredOnly MiniMax M2.1 measured
Design Arena: data viz1207Not measuredOnly MiniMax M2.1 measured
Design Arena: 3D1166Not measuredOnly MiniMax M2.1 measured
Design Arena: all code categories1190Not measuredOnly MiniMax M2.1 measured
Design Arena: SVG1131Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-A3BLeader
MedScribe (Vals AI)80.8%Not measuredOnly MiniMax M2.1 measured
IFBench69.9%72.5%Qwen3.5-35B-A3B
Long context reasoning (AA-LCR)67.7%72.0%Qwen3.5-35B-A3B
DTBenchNot measured80.0%Only Qwen3.5-35B-A3B measured
LMCANot measured29.5%Only Qwen3.5-35B-A3B measured
LMArena TextNot measured1395Only Qwen3.5-35B-A3B measured
LMArena Text: instruction followingNot measured1379Only Qwen3.5-35B-A3B measured
LMArena Text: creative writingNot measured1347Only Qwen3.5-35B-A3B measured
LMArena Text: EnglishNot measured1407Only Qwen3.5-35B-A3B measured
LMArena Text: non-EnglishNot measured1378Only Qwen3.5-35B-A3B measured
LMArena Text: ChineseNot measured1456Only Qwen3.5-35B-A3B measured
LMArena Text: GermanNot measured1367Only Qwen3.5-35B-A3B measured
LMArena Text: JapaneseNot measured1326Only Qwen3.5-35B-A3B measured
LMArena Text: KoreanNot measured1354Only Qwen3.5-35B-A3B measured
LMArena Text: FrenchNot measured1413Only Qwen3.5-35B-A3B measured
LMArena Text: SpanishNot measured1390Only Qwen3.5-35B-A3B measured
LMArena Text: RussianNot measured1377Only Qwen3.5-35B-A3B measured
LMArena Text: PolishNot measured1385Only Qwen3.5-35B-A3B measured
LMArena Text: multi-turnNot measured1390Only Qwen3.5-35B-A3B measured
LMArena Text: longer queriesNot measured1389Only Qwen3.5-35B-A3B measured
LMArena Text: writing and languageNot measured1365Only Qwen3.5-35B-A3B measured
LMArena Text: entertainment and mediaNot measured1347Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for MiniMax M2.1 and Qwen3.5-35B-A3B
BenchmarkMiniMax M2.1Qwen3.5-35B-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 M2.1$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 M2.1$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 M2.1$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 M2.1 and Qwen3.5-35B-A3B
SpecificationMiniMax M2.1Qwen3.5-35B-A3B
MakerMiniMaxQwen
WeightsOpen weightsOpen weights
ReleasedDecember 23, 2025February 25, 2026
Context window205K262K
Input $/Mtok$0.30$0.1625
Output $/Mtok$1.20$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it11
Cost per solved task$0.59Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.1 better than Qwen3.5-35B-A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M2.1 for output tokens 1.1x cheaper ($1.20 vs $1.30 per million) and work measured by τ²-Bench Telecom or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, MiniMax M2.1 or Qwen3.5-35B-A3B?

MiniMax M2.1 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 M2.1 only.

Which has the bigger context window, MiniMax M2.1 or Qwen3.5-35B-A3B?

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

How many benchmarks is the MiniMax M2.1 vs Qwen3.5-35B-A3B comparison based on?

8 benchmarks have a result for both models as of October 23, 2026. MiniMax M2.1's coding index rests on 1 independent benchmark 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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