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MiniMax M2.1 vs Qwen3 235B A22B Instruct 2507

MiniMax M2.1 leads Qwen3 235B A22B Instruct 2507 on the Artificial Analysis Intelligence Index, 20.9 to 12.0, and Qwen3 235B A22B Instruct 2507 costs 1.5x less per output token ($0.775 vs $1.20 per million). Updated October 23, 2026; 17 benchmarks have a result for both.

Replace MiniMax M2.1 Replace Qwen3 235B A22B Instruct 2507
MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
14
Qwen3 235B A22B Instruct 2507Qwen
Coding
No data
Overall
No data
Output $/M
$0.775
3
vs boards won of 17 shared

MiniMax M2.1 or Qwen3 235B A22B Instruct 2507: 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 AA Math Index or AIME 2025 (Artificial Analysis run), where it leads.

Model AMiniMax M2.1MiniMaxNot benchmarked1 independent benchmark$0.59 per solved taskModel BQwen3 235B A22B Instruct 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
17
MiniMax M2.1 only
17
Qwen3 235B A22B Instruct 2507 only
7
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 M2.1 not benchmarked, Qwen3 235B A22B Instruct 2507 not benchmarked.
Widest category
Agentic work, 32.2 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: MiniMax M2.1 85.4% against Qwen3 235B A22B Instruct 2507 53.2%, 32.2 points apart on a 0 to 100 scale.
Output price
MiniMax M2.1 $1.20 against Qwen3 235B A22B Instruct 2507 $0.775 per million output tokens, 1.5x apart.
Context window
MiniMax M2.1 takes 205K tokens, Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507Ties
Coding20
Intelligence10
Agentic work10
Reasoning20
Math02
Knowledge10
Web design60
General11
All shared boards143
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for MiniMax M2.1 and Qwen3 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
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%78.8%MiniMax M2.1
SciCodeNot measured41.4%Only Qwen3 235B A22B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)28.8%15.2%MiniMax M2.1
Terminal-Bench36.6%Not measuredOnly MiniMax M2.1 measured
WeirdMLNot measured38.7%Only Qwen3 235B A22B Instruct 2507 measured
ALE-Bench623.8Not measuredOnly MiniMax M2.1 measured
Neither model has a result on the other 35 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for MiniMax M2.1 and Qwen3 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
AA Intelligence Index20.912.0MiniMax M2.1
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for MiniMax M2.1 and Qwen3 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
τ²-Bench Telecom85.4%53.2%MiniMax M2.1
Berkeley Function Calling Leaderboard (BFCL)Not measured52.1%Only Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for MiniMax M2.1 and Qwen3 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
GPQA Diamond78.5%Not measuredOnly MiniMax M2.1 measured
GPQA Diamond (Artificial Analysis run)83.0%79.0%MiniMax M2.1
Humanity's Last Exam (Artificial Analysis run)23.2%15.9%MiniMax M2.1
ARC-AGINot measured11.0%Only Qwen3 235B A22B Instruct 2507 measured
ARC-AGI-2Not measured1.3%Only Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 18 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for MiniMax M2.1 and Qwen3 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
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 Index82.791.0Qwen3 235B A22B Instruct 2507
AIME 2025 (Artificial Analysis run)82.7%91.0%Qwen3 235B A22B Instruct 2507
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for MiniMax M2.1 and Qwen3 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
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%84.3%MiniMax M2.1
Neither model has a result on the other 12 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for MiniMax M2.1 and Qwen3 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
Design Arena: websites12011058MiniMax M2.1
Design Arena: UI components1220963MiniMax M2.1
Design Arena: game dev1134951MiniMax M2.1
Design Arena: data viz12071070MiniMax M2.1
Design Arena: 3D1166995MiniMax M2.1
Design Arena: all code categories11901038MiniMax M2.1
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 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
MedScribe (Vals AI)80.8%Not measuredOnly MiniMax M2.1 measured
IFBench69.9%51.2%MiniMax M2.1
Long context reasoning (AA-LCR)67.7%72.0%Qwen3 235B A22B Instruct 2507
DTBenchNot measured78.4%Only Qwen3 235B A22B Instruct 2507 measured
LMCANot measured23.5%Only Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 43 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 235B A22B Instruct 2507
BenchmarkMiniMax M2.1Qwen3 235B A22B Instruct 2507Leader
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 235B A22B Instruct 2507$0.0005Fits in one request

Qwen3 235B A22B Instruct 2507 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.1$0.019Fits in one request
Qwen3 235B A22B Instruct 2507$0.0096Fits in one request

Qwen3 235B A22B Instruct 2507 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.1$0.072Exceeds the context window
Qwen3 235B A22B Instruct 2507$0.037Fits in one request

Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507
SpecificationMiniMax M2.1Qwen3 235B A22B Instruct 2507
MakerMiniMaxQwen
WeightsOpen weightsOpen weights
ReleasedDecember 23, 2025July 21, 2025
Context window205K262K
Input $/Mtok$0.30$0.145
Output $/Mtok$1.20$0.775
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 235B A22B Instruct 2507 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 AA Math Index or AIME 2025 (Artificial Analysis run), where it leads.

Which is cheaper, MiniMax M2.1 or Qwen3 235B A22B Instruct 2507?

MiniMax M2.1 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3 235B A22B Instruct 2507 costs $0.145 and $0.775. Cost per solved task is known for MiniMax M2.1 only.

Which has the bigger context window, MiniMax M2.1 or Qwen3 235B A22B Instruct 2507?

Qwen3 235B A22B Instruct 2507, with 262K tokens against 205K.

How many benchmarks is the MiniMax M2.1 vs Qwen3 235B A22B Instruct 2507 comparison based on?

17 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 235B A22B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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