Enter opens the highlighted result. Esc closes.

MiniMax M2.7 vs Qwen3 235B A22B Thinking 2507

MiniMax M2.7 leads Qwen3 235B A22B Thinking 2507 on the Artificial Analysis Intelligence Index, 22.8 to 12.7, and MiniMax M2.7 costs 2.9x less per output token ($1.20 vs $3.50 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Qwen3 235B A22B Thinking 2507
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
19
Qwen3 235B A22B Thinking 2507Qwen
Coding
No data
Overall
52.9
Output $/M
$3.50
18
vs boards won of 37 shared

MiniMax M2.7 or Qwen3 235B A22B Thinking 2507: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Qwen3 235B A22B Thinking 2507 has none, so the two cannot be ranked on coding.

Pick Qwen3 235B A22B Thinking 2507 for work measured by WeirdML or LMArena Text: expert, where it leads.

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BQwen3 235B A22B Thinking 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
37
MiniMax M2.7 only
37
Qwen3 235B A22B Thinking 2507 only
9
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 M2.7 36.2 from 3 benchmarks, Qwen3 235B A22B Thinking 2507 not benchmarked.
Widest category
Web design, 28.9 points apart on average over 6 shared benchmarks.
Widest single gap
Design Arena: data viz: MiniMax M2.7 1233 against Qwen3 235B A22B Thinking 2507 950, 35.4 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Qwen3 235B A22B Thinking 2507 $3.50 per million output tokens, 2.9x apart.
Context window
MiniMax M2.7 takes 205K 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 M2.7BarsQwen3 235B A22B Thinking 2507Ties
Coding31
Intelligence10
Agentic work10
Reasoning21
Math20
Knowledge04
Web design60
General412
All shared boards1918
CodingLike-for-likeSix of these boards feed the Vibe Coding Index31
Coding benchmarks for MiniMax M2.7 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 235B A22B Thinking 2507Leader
LMArena WebDev1399Not measuredOnly MiniMax M2.7 measured
AA Coding Index52.622.1MiniMax M2.7
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%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench45.1%Not measuredOnly MiniMax M2.7 measured
WeirdML37.0%41.0%Qwen3 235B A22B Thinking 2507
ALE-Bench599.3Not measuredOnly MiniMax M2.7 measured
LMArena Text: coding14541424MiniMax M2.7
LMArena Text: software and IT14461431MiniMax M2.7
LMArena WebDev: React1388Not measuredOnly MiniMax M2.7 measured
LMArena WebDev: HTML1401Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for MiniMax M2.7 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 235B A22B Thinking 2507Leader
AA Intelligence Index22.812.7MiniMax M2.7
Epoch Capabilities Index145.8Not measuredOnly MiniMax M2.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for MiniMax M2.7 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 235B A22B Thinking 2507Leader
AA Agentic Index15.31.3MiniMax M2.7
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%Not measuredOnly MiniMax M2.7 measured
Vending-Bench 2Not measured-$11Only Qwen3 235B A22B Thinking 2507 measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
Reasoning benchmarks for MiniMax M2.7 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 235B A22B Thinking 2507Leader
GPQA Diamond86.6%Not measuredOnly MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)87.4%Not measuredOnly MiniMax M2.7 measured
Humanity's Last Exam (Artificial Analysis run)29.6%Not measuredOnly MiniMax M2.7 measured
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 prompts14221416MiniMax M2.7
LMArena Text: expert14431463Qwen3 235B A22B Thinking 2507
LMArena Text: hard prompts in English14411432MiniMax M2.7
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for MiniMax M2.7 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 235B A22B Thinking 2507Leader
AIME91.0%Not measuredOnly MiniMax M2.7 measured
OTIS Mock AIMENot measured86.7%Only Qwen3 235B A22B Thinking 2507 measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math14211412MiniMax M2.7
LMArena Text: mathematical work14371435MiniMax M2.7
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for MiniMax M2.7 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 235B A22B Thinking 2507Leader
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
SimpleQA VerifiedNot measured40.4%Only Qwen3 235B A22B Thinking 2507 measured
LMArena Text: science14161433Qwen3 235B A22B Thinking 2507
LMArena Text: medicine and healthcare14091456Qwen3 235B A22B Thinking 2507
LMArena Text: legal and government14031415Qwen3 235B A22B Thinking 2507
LMArena Text: business and finance14071413Qwen3 235B A22B Thinking 2507
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for MiniMax M2.7 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 235B A22B Thinking 2507Leader
Design Arena: websites12421052MiniMax M2.7
Design Arena: UI components1207942MiniMax M2.7
Design Arena: game dev1209956MiniMax M2.7
Design Arena: data viz1233950MiniMax M2.7
Design Arena: 3D1194997MiniMax M2.7
Design Arena: all code categories12331032MiniMax M2.7
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 index412
General benchmarks for MiniMax M2.7 and Qwen3 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 235B A22B Thinking 2507Leader
MedScribe (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
IFBench75.7%Not measuredOnly MiniMax M2.7 measured
Long context reasoning (AA-LCR)78.3%Not measuredOnly MiniMax M2.7 measured
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
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text14051415Qwen3 235B A22B Thinking 2507
LMArena Text: instruction following14051386MiniMax M2.7
LMArena Text: creative writing13541384Qwen3 235B A22B Thinking 2507
LMArena Text: English14261429Qwen3 235B A22B Thinking 2507
LMArena Text: non-English13821397Qwen3 235B A22B Thinking 2507
LMArena Text: Chinese14421481Qwen3 235B A22B Thinking 2507
LMArena Text: German13981408Qwen3 235B A22B Thinking 2507
LMArena Text: Japanese12601386Qwen3 235B A22B Thinking 2507
LMArena Text: Korean13141375Qwen3 235B A22B Thinking 2507
LMArena Text: French1424Not measuredOnly MiniMax M2.7 measured
LMArena Text: Spanish14021389MiniMax M2.7
LMArena Text: Russian13831401Qwen3 235B A22B Thinking 2507
LMArena Text: Polish13871390Qwen3 235B A22B Thinking 2507
LMArena Text: multi-turn14121406MiniMax M2.7
LMArena Text: longer queries14181400MiniMax M2.7
LMArena Text: writing and language13761388Qwen3 235B A22B Thinking 2507
LMArena Text: entertainment and media13601370Qwen3 235B A22B Thinking 2507
Neither model has a result on the other 23 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 235B A22B Thinking 2507
BenchmarkMiniMax M2.7Qwen3 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 M2.7$0.0009Fits in one request
Qwen3 235B A22B Thinking 2507$0.0022Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Qwen3 235B A22B Thinking 2507$0.033Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Qwen3 235B A22B Thinking 2507$0.125Exceeds the context window

MiniMax M2.7 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 235B A22B Thinking 2507
SpecificationMiniMax M2.7Qwen3 235B A22B Thinking 2507
MakerMiniMaxQwen
WeightsOpen weightsOpen weights
ReleasedMarch 18, 2026July 25, 2025
Context window205K128K
Input $/Mtok$0.30$0.45
Output $/Mtok$1.20$3.50
Coding index36.2Not benchmarked
Independent measurements behind it30
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than Qwen3 235B A22B Thinking 2507 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Qwen3 235B A22B Thinking 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 235B A22B Thinking 2507 for work measured by WeirdML or LMArena Text: expert, where it leads.

Which is cheaper, MiniMax M2.7 or Qwen3 235B A22B Thinking 2507?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3 235B A22B Thinking 2507 costs $0.45 and $3.50. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Qwen3 235B A22B Thinking 2507?

MiniMax M2.7, with 205K tokens against 128K.

How many benchmarks is the MiniMax M2.7 vs Qwen3 235B A22B Thinking 2507 comparison based on?

37 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 235B A22B Thinking 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next