MiniMax M2.7 vs Qwen3.8 2.4T A95B

Qwen3.8 2.4T A95B leads MiniMax M2.7 on the Artificial Analysis Intelligence Index, 39.9 to 22.8, and MiniMax M2.7 costs 5.0x less per output token ($1.20 vs $6.00 per million). Updated October 23, 2026; 7 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Qwen3.8 2.4T A95B

MiniMax M2.7MiniMax

Coding: 36.2
Overall: 44.5
Output $/M: $1.20

Qwen3.8 2.4T A95BQwen

Coding: No data
Overall: No data
Output $/M: $6.00

vs boards won of 7 shared

MiniMax M2.7 or Qwen3.8 2.4T A95B: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Qwen3.8 2.4T A95B has none, so the two cannot be ranked on coding.

Pick Qwen3.8 2.4T A95B for a larger context window (1.05M against 205K tokens) and work measured by AA Coding Index or SciCode, where it leads.

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task Model BQwen3.8 2.4T A95BQwenNot benchmarkedNo coding benchmarkNo cost per solved task

7672

Shared results: 7
MiniMax M2.7 only: 67
Qwen3.8 2.4T A95B only: 2
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.

Coding
Vibe Coding Index, six public coding benchmarks
No call
Only MiniMax M2.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B leads, 39.9 against 22.8.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B leads, 50.1 against 15.3.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only MiniMax M2.7 has a GPQA Diamond result, 86.6%.
Directional only
Math
AIME
No call
Only MiniMax M2.7 has a AIME result, 91.0%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.7 has a MMLU Pro result, 80.4%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2.7 has a Design Arena: websites result, 1242.
Directional only
Long documents
Listed context window
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
MiniMax M2.7
MiniMax M2.7 $0.0009, Qwen3.8 2.4T A95B $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.7 has the number, $0.64.
Directional only

At a glance

Coding index: MiniMax M2.7 36.2 from 3 benchmarks, Qwen3.8 2.4T A95B not benchmarked.
Widest category: Agentic work, 34.8 points apart on average over 1 shared benchmark.
Widest single gap: AA Agentic Index: MiniMax M2.7 15.3 against Qwen3.8 2.4T A95B 50.1, 34.8 points apart on a 0 to 100 scale.
Output price: MiniMax M2.7 $1.20 against Qwen3.8 2.4T A95B $6.00 per million output tokens, 5.0x apart.
Context window: MiniMax M2.7 takes 205K tokens, Qwen3.8 2.4T A95B 1.05M.

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
Category	MiniMax M2.7	Bars	Qwen3.8 2.4T A95B	Ties
Coding	0		2
Intelligence	0		1
Agentic work	0		1
Reasoning	0		2
General	0		1
All shared boards	0		7

CodingLike-for-likeSix of these boards feed the Vibe Coding Index02

Coding benchmarks for MiniMax M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
LMArena WebDev	1398	Not measured	Only MiniMax M2.7 measured
AA Coding Index	52.6	71.9	Qwen3.8 2.4T A95B
LiveCodeBench (Vals AI)	79.9%	Not measured	Only MiniMax M2.7 measured
SWE-bench Verified (Vals AI)	73.8%	Not measured	Only MiniMax M2.7 measured
Vibe Code Bench (Vals AI)	11.9%	Not measured	Only MiniMax M2.7 measured
Code migration (Vals AI)	8.7%	Not measured	Only MiniMax M2.7 measured
ProgramBench (Vals AI)	0.0%	Not measured	Only MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)	48.7%	Not measured	Only MiniMax M2.7 measured
SciCode	50.1%	54.1%	Qwen3.8 2.4T A95B
Terminal-Bench Hard (Artificial Analysis run)	39.4%	Not measured	Only MiniMax M2.7 measured
Terminal-Bench	45.1%	Not measured	Only MiniMax M2.7 measured
WeirdML	37.0%	Not measured	Only MiniMax M2.7 measured
ALE-Bench	599.3	Not measured	Only MiniMax M2.7 measured
LMArena Text: coding	1454	Not measured	Only MiniMax M2.7 measured
LMArena Text: software and IT	1445	Not measured	Only MiniMax M2.7 measured
LMArena WebDev: React	1388	Not measured	Only MiniMax M2.7 measured
LMArena WebDev: HTML	1402	Not measured	Only 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 index01

Intelligence benchmarks for MiniMax M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
AA Intelligence Index	22.8	39.9	Qwen3.8 2.4T A95B
Epoch Capabilities Index	145.8	Not measured	Only MiniMax M2.7 measured

Agentic workLike-for-likePublic boards, shown as published, kept out of the index01

Agentic work benchmarks for MiniMax M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
AA Agentic Index	15.3	50.1	Qwen3.8 2.4T A95B
Finance Agent (Vals AI)	27.9%	Not measured	Only MiniMax M2.7 measured
Tax Agent Bench (Vals AI)	6.9%	Not measured	Only MiniMax M2.7 measured
Legal Research Bench (Vals AI)	10.6%	Not measured	Only MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)	28.4%	Not measured	Only MiniMax M2.7 measured
τ²-Bench Telecom	84.8%	Not measured	Only MiniMax M2.7 measured
MCP Atlas	Not measured	84.5%	Only Qwen3.8 2.4T A95B measured
Neither model has a result on the other 35 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index02

Reasoning benchmarks for MiniMax M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
GPQA Diamond	86.6%	Not measured	Only MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)	87.4%	93.5%	Qwen3.8 2.4T A95B
Humanity's Last Exam (Artificial Analysis run)	29.6%	42.4%	Qwen3.8 2.4T A95B
LMArena Text: hard prompts	1423	Not measured	Only MiniMax M2.7 measured
LMArena Text: expert	1443	Not measured	Only MiniMax M2.7 measured
LMArena Text: hard prompts in English	1441	Not measured	Only MiniMax M2.7 measured
Neither model has a result on the other 17 boards here

MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared

Math benchmarks for MiniMax M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
AIME	91.0%	Not measured	Only MiniMax M2.7 measured
ProofBench	3.0%	Not measured	Only MiniMax M2.7 measured
LMArena Text: math	1421	Not measured	Only MiniMax M2.7 measured
LMArena Text: mathematical work	1437	Not measured	Only MiniMax M2.7 measured
MathArena	Not measured	31.6%	Only Qwen3.8 2.4T A95B measured
Neither model has a result on the other 9 boards here

KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared

Knowledge benchmarks for MiniMax M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
MMLU Pro	80.4%	Not measured	Only MiniMax M2.7 measured
LegalBench (Vals AI)	84.0%	Not measured	Only MiniMax M2.7 measured
CaseLaw (Vals AI)	60.9%	Not measured	Only MiniMax M2.7 measured
CorpFin (Vals AI)	61.2%	Not measured	Only MiniMax M2.7 measured
TaxEval (Vals AI)	66.6%	Not measured	Only MiniMax M2.7 measured
MedCode (Vals AI)	34.4%	Not measured	Only MiniMax M2.7 measured
LMArena Text: science	1416	Not measured	Only MiniMax M2.7 measured
LMArena Text: medicine and healthcare	1409	Not measured	Only MiniMax M2.7 measured
LMArena Text: legal and government	1403	Not measured	Only MiniMax M2.7 measured
LMArena Text: business and finance	1407	Not measured	Only MiniMax M2.7 measured
Neither model has a result on the other 10 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared

Web design benchmarks for MiniMax M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
Design Arena: websites	1242	Not measured	Only MiniMax M2.7 measured
Design Arena: UI components	1208	Not measured	Only MiniMax M2.7 measured
Design Arena: game dev	1209	Not measured	Only MiniMax M2.7 measured
Design Arena: data viz	1233	Not measured	Only MiniMax M2.7 measured
Design Arena: 3D	1194	Not measured	Only MiniMax M2.7 measured
Design Arena: all code categories	1233	Not measured	Only MiniMax M2.7 measured
Design Arena: SVG	1136	Not measured	Only MiniMax M2.7 measured
Design Arena: ASCII art	1136	Not measured	Only 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 index01

General benchmarks for MiniMax M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
MedScribe (Vals AI)	79.9%	Not measured	Only MiniMax M2.7 measured
IFBench	75.7%	Not measured	Only MiniMax M2.7 measured
Long context reasoning (AA-LCR)	78.3%	80.3%	Qwen3.8 2.4T A95B
ExploitBench	13.3%	Not measured	Only MiniMax M2.7 measured
LMArena Text	1405	Not measured	Only MiniMax M2.7 measured
LMArena Text: instruction following	1405	Not measured	Only MiniMax M2.7 measured
LMArena Text: creative writing	1354	Not measured	Only MiniMax M2.7 measured
LMArena Text: English	1426	Not measured	Only MiniMax M2.7 measured
LMArena Text: non-English	1383	Not measured	Only MiniMax M2.7 measured
LMArena Text: Chinese	1441	Not measured	Only MiniMax M2.7 measured
LMArena Text: German	1398	Not measured	Only MiniMax M2.7 measured
LMArena Text: Japanese	1259	Not measured	Only MiniMax M2.7 measured
LMArena Text: Korean	1316	Not measured	Only MiniMax M2.7 measured
LMArena Text: French	1424	Not measured	Only MiniMax M2.7 measured
LMArena Text: Spanish	1403	Not measured	Only MiniMax M2.7 measured
LMArena Text: Russian	1384	Not measured	Only MiniMax M2.7 measured
LMArena Text: Polish	1388	Not measured	Only MiniMax M2.7 measured
LMArena Text: multi-turn	1412	Not measured	Only MiniMax M2.7 measured
LMArena Text: longer queries	1419	Not measured	Only MiniMax M2.7 measured
LMArena Text: writing and language	1376	Not measured	Only MiniMax M2.7 measured
LMArena Text: entertainment and media	1361	Not measured	Only MiniMax M2.7 measured
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 M2.7 and Qwen3.8 2.4T A95B
Benchmark	MiniMax M2.7	Qwen3.8 2.4T A95B	Leader
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

Qwen3.8 2.4T A95B$0.0050Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request

Qwen3.8 2.4T A95B$0.118Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window

Qwen3.8 2.4T A95B$0.460Fits in one request

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 Qwen3.8 2.4T A95B
Specification	MiniMax M2.7	Qwen3.8 2.4T A95B
Maker	MiniMax	Qwen
Weights	Open weights	Open weights
Released	March 18, 2026	August 12, 2026
Context window	205K	1.05M
Input $/Mtok	$0.30	$2.00
Output $/Mtok	$1.20	$6.00
Coding index	36.2	Not benchmarked
Independent measurements behind it	3	0
Cost per solved task	$0.64	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is MiniMax M2.7 better than Qwen3.8 2.4T A95B for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Qwen3.8 2.4T A95B has none, so the two cannot be ranked on coding. Pick Qwen3.8 2.4T A95B for a larger context window (1.05M against 205K tokens) and work measured by AA Coding Index or SciCode, where it leads.

Which is cheaper, MiniMax M2.7 or Qwen3.8 2.4T A95B?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3.8 2.4T A95B costs $2.00 and $6.00. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Qwen3.8 2.4T A95B?

Qwen3.8 2.4T A95B, with 1.05M tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs Qwen3.8 2.4T A95B comparison based on?

7 benchmarks have a result for both models as of October 23, 2026. MiniMax M2.7's coding index rests on 3 independent benchmarks and Qwen3.8 2.4T A95B's on 0. Where only one model has a result, the page says so instead of naming a winner.

MiniMax M2.7 or Qwen3.8 2.4T A95B: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

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