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MiniMax M2.1 vs Qwen3.6 35B A3B

MiniMax M2.1 leads Qwen3.6 35B A3B on the Artificial Analysis Intelligence Index, 20.9 to 18.2, and Qwen3.6 35B A3B costs 1.2x less per output token ($1.00 vs $1.20 per million). Updated October 22, 2026; 8 benchmarks have a result for both.

MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
4
Qwen3.6 35B A3BQwen
Coding
No data
Overall
45.0
Output $/M
$1.00
4
vs boards won of 8 shared

MiniMax M2.1 or Qwen3.6 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 work measured by Terminal-Bench Hard (Artificial Analysis run) or τ²-Bench Telecom, where it leads.

Shared results
8
MiniMax M2.1 only
26
Qwen3.6 35B A3B only
12
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, Qwen3.6 35B A3B not benchmarked.
Widest category
Agentic work, 9.9 points apart on average over 1 shared benchmark.
Widest single gap
Terminal-Bench: MiniMax M2.1 36.6% against Qwen3.6 35B A3B 24.6%, 12.0 points apart on a 0 to 100 scale.
Output price
MiniMax M2.1 $1.20 against Qwen3.6 35B A3B $1.00 per million output tokens, 1.2x apart.
Context window
MiniMax M2.1 takes 205K tokens, Qwen3.6 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 M2.1BarsQwen3.6 35B A3BTies
Coding11
Intelligence10
Agentic work01
Reasoning11
General11
All shared boards44
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
Coding benchmarks for MiniMax M2.1 and Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 35B A3BLeader
AA Coding IndexNot measured41.9Only Qwen3.6 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
SciCodeNot measured36.6%Only Qwen3.6 35B A3B measured
Terminal-Bench Hard (Artificial Analysis run)28.8%34.8%Qwen3.6 35B A3B
Terminal-Bench36.6%24.6%MiniMax M2.1
WeirdMLNot measured34.5%Only Qwen3.6 35B A3B measured
ALE-Bench623.8Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 34 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for MiniMax M2.1 and Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 35B A3BLeader
AA Intelligence Index20.918.2MiniMax M2.1
Epoch Capabilities IndexNot measured143.7Only Qwen3.6 35B A3B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for MiniMax M2.1 and Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 35B A3BLeader
AA Agentic IndexNot measured13.1Only Qwen3.6 35B A3B measured
τ²-Bench Telecom85.4%95.3%Qwen3.6 35B A3B
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 Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 35B A3BLeader
GPQA Diamond78.5%Not measuredOnly MiniMax M2.1 measured
GPQA Diamond (Artificial Analysis run)83.0%84.1%Qwen3.6 35B A3B
Humanity's Last Exam (Artificial Analysis run)23.2%22.2%MiniMax M2.1
GPQA Diamond (Epoch AI run)Not measured84.8%Only Qwen3.6 35B A3B measured
Mystery game puzzlesNot measured22.0%Only Qwen3.6 35B A3B measured
Neither model has a result on the other 18 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for MiniMax M2.1 and Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 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 measured86.7%Only Qwen3.6 35B A3B measured
FrontierMath, tiers 1 to 3Not measured20.4%Only Qwen3.6 35B A3B measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Knowledge benchmarks for MiniMax M2.1 and Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 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
Neither model has a result on the other 12 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 Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 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 viz1206Not measuredOnly MiniMax M2.1 measured
Design Arena: 3D1164Not 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 index11
General benchmarks for MiniMax M2.1 and Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 35B A3BLeader
MedScribe (Vals AI)80.8%Not measuredOnly MiniMax M2.1 measured
IFBench69.9%64.4%MiniMax M2.1
Long context reasoning (AA-LCR)67.7%71.7%Qwen3.6 35B A3B
DTBenchNot measured73.9%Only Qwen3.6 35B A3B measured
LMCANot measured29.7%Only Qwen3.6 35B A3B measured
Surface Evolver BenchNot measured44.4%Only Qwen3.6 35B A3B measured
Neither model has a result on the other 42 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 Qwen3.6 35B A3B
BenchmarkMiniMax M2.1Qwen3.6 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
Qwen3.6 35B A3B$0.0006Fits in one request

Qwen3.6 35B A3B costs less

Repository review

50K input + 3K output tokens

MiniMax M2.1$0.019Fits in one request
Qwen3.6 35B A3B$0.0080Fits in one request

Qwen3.6 35B A3B costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.1$0.072Exceeds the context window
Qwen3.6 35B A3B$0.030Fits in one request

Qwen3.6 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 Qwen3.6 35B A3B
SpecificationMiniMax M2.1Qwen3.6 35B A3B
MakerMiniMaxQwen
WeightsOpen weightsOpen weights
ReleasedDecember 23, 2025April 27, 2026
Context window205K262K
Input $/Mtok$0.30$0.10
Output $/Mtok$1.20$1.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved task$0.59Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.1 better than Qwen3.6 35B A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M2.1 for work measured by Terminal-Bench Hard (Artificial Analysis run) or τ²-Bench Telecom, where it leads.

Which is cheaper, MiniMax M2.1 or Qwen3.6 35B A3B?

MiniMax M2.1 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3.6 35B A3B costs $0.10 and $1.00. Cost per solved task is known for MiniMax M2.1 only.

Which has the bigger context window, MiniMax M2.1 or Qwen3.6 35B A3B?

Qwen3.6 35B A3B, with 262K tokens against 205K.

How many benchmarks is the MiniMax M2.1 vs Qwen3.6 35B A3B comparison based on?

8 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.1's coding index rests on 1 independent benchmark and Qwen3.6 35B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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