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MiniMax M1 vs Qwen3 235B A22B Thinking 2507

Qwen3 235B A22B Thinking 2507 leads MiniMax M1 on the Artificial Analysis Intelligence Index, 12.7 to 11.7, and MiniMax M1 costs 1.6x less per output token ($2.20 vs $3.50 per million). Updated October 23, 2026; 28 benchmarks have a result for both.

MiniMax M1MiniMax
Coding
No data
Overall
No data
Output $/M
$2.20
0
Qwen3 235B A22B Thinking 2507Qwen
Coding
No data
Overall
52.9
Output $/M
$3.50
28
vs boards won of 28 shared

MiniMax M1 or Qwen3 235B A22B Thinking 2507: which to pick

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

Pick MiniMax M1 for output tokens 1.6x cheaper ($2.20 vs $3.50 per million) and a larger context window (1M against 128K tokens).

Shared results
28
MiniMax M1 only
1
Qwen3 235B A22B Thinking 2507 only
18
Like-for-like categories
6 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 M1 not benchmarked, Qwen3 235B A22B Thinking 2507 not benchmarked.
Widest category
Reasoning, 16.7 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena Text: Japanese: MiniMax M1 1218 against Qwen3 235B A22B Thinking 2507 1386, 28.1 points apart on a 0 to 100 scale.
Output price
MiniMax M1 $2.20 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 1.6x apart.
Context window
MiniMax M1 takes 1M tokens, Qwen3 235B A22B Thinking 2507 128K.

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 M1BarsQwen3 235B A22B Thinking 2507Ties
Coding02
Intelligence01
Reasoning03
Math02
Knowledge04
General016
All shared boards028
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for MiniMax M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 2507Leader
AA Coding IndexNot measured22.1Only Qwen3 235B A22B Thinking 2507 measured
WeirdMLNot measured41.0%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: coding13591424Qwen3 235B A22B Thinking 2507
LMArena Text: software and IT13591431Qwen3 235B A22B Thinking 2507
Neither model has a result on the other 39 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for MiniMax M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 2507Leader
AA Intelligence Index11.712.7Qwen3 235B A22B Thinking 2507
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for MiniMax M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 2507Leader
AA Agentic IndexNot measured1.3Only Qwen3 235B A22B Thinking 2507 measured
Vending-Bench 2Not measured-$11Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for MiniMax M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 2507Leader
GPQA Diamond (Epoch AI run)Not measured80.1%Only Qwen3 235B A22B Thinking 2507 measured
Mystery game puzzlesNot measured9.0%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: hard prompts13391416Qwen3 235B A22B Thinking 2507
LMArena Text: expert13171463Qwen3 235B A22B Thinking 2507
LMArena Text: hard prompts in English13531432Qwen3 235B A22B Thinking 2507
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 M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 2507Leader
OTIS Mock AIMENot measured86.7%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: math13611412Qwen3 235B A22B Thinking 2507
LMArena Text: mathematical work13631435Qwen3 235B A22B Thinking 2507
Neither model has a result on the other 11 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for MiniMax M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 2507Leader
SimpleQA VerifiedNot measured40.4%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: science13541433Qwen3 235B A22B Thinking 2507
LMArena Text: medicine and healthcare13551456Qwen3 235B A22B Thinking 2507
LMArena Text: legal and government13371415Qwen3 235B A22B Thinking 2507
LMArena Text: business and finance13191412Qwen3 235B A22B Thinking 2507
Neither model has a result on the other 15 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for MiniMax M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 2507Leader
Design Arena: websitesNot measured1052Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: UI componentsNot measured942Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: game devNot measured956Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: data vizNot measured950Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: 3DNot measured998Only Qwen3 235B A22B Thinking 2507 measured
Design Arena: all code categoriesNot measured1032Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index016
General benchmarks for MiniMax M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 2507Leader
DTBenchNot measured80.3%Only Qwen3 235B A22B Thinking 2507 measured
LMCANot measured29.3%Only Qwen3 235B A22B Thinking 2507 measured
Fiction.LiveBenchNot measured75.0%Only Qwen3 235B A22B Thinking 2507 measured
Creative writing (Lech Mazur)Not measured82.4%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text13431415Qwen3 235B A22B Thinking 2507
LMArena Text: instruction following13121386Qwen3 235B A22B Thinking 2507
LMArena Text: creative writing12971384Qwen3 235B A22B Thinking 2507
LMArena Text: English13631429Qwen3 235B A22B Thinking 2507
LMArena Text: non-English13191397Qwen3 235B A22B Thinking 2507
LMArena Text: Chinese13601481Qwen3 235B A22B Thinking 2507
LMArena Text: German13501408Qwen3 235B A22B Thinking 2507
LMArena Text: Japanese12181386Qwen3 235B A22B Thinking 2507
LMArena Text: Korean12661375Qwen3 235B A22B Thinking 2507
LMArena Text: French1370Not measuredOnly MiniMax M1 measured
LMArena Text: Spanish13531389Qwen3 235B A22B Thinking 2507
LMArena Text: Russian13291400Qwen3 235B A22B Thinking 2507
LMArena Text: Polish13291390Qwen3 235B A22B Thinking 2507
LMArena Text: multi-turn13351406Qwen3 235B A22B Thinking 2507
LMArena Text: longer queries13261399Qwen3 235B A22B Thinking 2507
LMArena Text: writing and language13111388Qwen3 235B A22B Thinking 2507
LMArena Text: entertainment and media13031370Qwen3 235B A22B Thinking 2507
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for MiniMax M1 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M1Qwen3 235B A22B Thinking 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 M1$0.0015Fits in one request
Qwen3 235B A22B Thinking 2507$0.0022Fits in one request

MiniMax M1 costs less

Repository review

50K input + 3K output tokens

MiniMax M1$0.027Fits in one request
Qwen3 235B A22B Thinking 2507$0.033Fits in one request

MiniMax M1 costs less

Agent loop

200K input + 10K output tokens

MiniMax M1$0.102Fits in one request
Qwen3 235B A22B Thinking 2507$0.125Exceeds the context window

MiniMax M1 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 M1 and Qwen3 235B A22B Thinking 2507
SpecificationMiniMax M1Qwen3 235B A22B Thinking 2507
MakerMiniMaxQwen
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025July 25, 2025
Context window1M128K
Input $/Mtok$0.40$0.45
Output $/Mtok$2.20$3.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M1 better than Qwen3 235B A22B Thinking 2507 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M1 for output tokens 1.6x cheaper ($2.20 vs $3.50 per million) and a larger context window (1M against 128K tokens).

Which is cheaper, MiniMax M1 or Qwen3 235B A22B Thinking 2507?

MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for neither of them.

Which has the bigger context window, MiniMax M1 or Qwen3 235B A22B Thinking 2507?

MiniMax M1, with 1M tokens against 128K.

How many benchmarks is the MiniMax M1 vs Qwen3 235B A22B Thinking 2507 comparison based on?

28 benchmarks have a result for both models as of October 23, 2026. MiniMax M1's coding index rests on 0 independent benchmarks and Qwen3 235B A22B Thinking 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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