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MiniMax M2 vs Qwen3.8 27B

Updated October 21, 2026. 32 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace MiniMax M2 Replace Qwen3.8 27B
MiniMax M2MiniMax
Coding
45.3
Overall
18.6
Output $/M
$1.02
0
Qwen3.8 27BQwen
Coding
73.6
Overall
33.7
Output $/M
$1.35
32
vs boards won of 32 shared

Decision reading

Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 45.3 for MiniMax M2.

Pick MiniMax M2 when output tokens cost 1.3x less, or when a solved task costs $0.702 against $1.26.

Model AMiniMax M2MiniMax45.3/1002 independent benchmarks$0.702 per solved taskModel BQwen3.8 27BQwen73.6/1002 independent benchmarks$1.26 per solved task
Shared results
32
MiniMax M2 only
17
Qwen3.8 27B only
53
Like-for-like categories
6 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 45.3 from 2 benchmarks, Qwen3.8 27B 73.6 from 2 benchmarks.
Widest category
Coding, 30.6 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: MiniMax M2 1306 against Qwen3.8 27B 1570, 43.9 points apart on a 0 to 100 scale.
Output price
MiniMax M2 $1.02 against Qwen3.8 27B $1.35 per million output tokens, 1.3x apart.
Context window
MiniMax M2 takes 205K tokens, Qwen3.8 27B 1M.

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 M2BarsQwen3.8 27BTies
Coding04
Intelligence01
Reasoning05
Math02
Knowledge04
General016
All shared boards032
CodingLike-for-likeFour of these boards feed the Vibe Coding Index04
Coding benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
SWE-bench Verified61.0%Not measuredOnly MiniMax M2 measured
LiveBench codingNot measured86.8%Only Qwen3.8 27B measured
LMArena WebDev12971593Qwen3.8 27B
AA Coding IndexNot measured68.1Only Qwen3.8 27B measured
LiveCodeBench (Vals AI)Not measured84.0%Only Qwen3.8 27B measured
SWE-bench Verified (Vals AI)Not measured86.0%Only Qwen3.8 27B measured
Vibe Code Bench (Vals AI)Not measured64.8%Only Qwen3.8 27B measured
Code migration (Vals AI)Not measured14.2%Only Qwen3.8 27B measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
IOI (Vals AI)Not measured39.1%Only Qwen3.8 27B measured
Terminal-Bench 2.1 (Vals AI)Not measured58.4%Only Qwen3.8 27B measured
SkillsBench (Vals AI)Not measured38.1%Only Qwen3.8 27B measured
CyberBench (Vals AI)Not measured67.8%Only Qwen3.8 27B measured
LiveCodeBench (Artificial Analysis run)82.6%Not measuredOnly MiniMax M2 measured
SciCodeNot measured46.6%Only Qwen3.8 27B measured
Terminal-Bench Hard (Artificial Analysis run)25.8%Not measuredOnly MiniMax M2 measured
Terminal-Bench30.0%Not measuredOnly MiniMax M2 measured
LMArena Text: coding13711483Qwen3.8 27B
LMArena Text: software and IT13731478Qwen3.8 27B
LMArena WebDev: ReactNot measured1602Only Qwen3.8 27B measured
LMArena WebDev: HTML13061570Qwen3.8 27B
LMArena WebDev: from an imageNot measured1577Only Qwen3.8 27B measured
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
AA Intelligence Index18.633.7Qwen3.8 27B
Epoch Capabilities IndexNot measured151.7Only Qwen3.8 27B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Agentic work benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
AA Agentic IndexNot measured45.8Only Qwen3.8 27B measured
LiveBench researchNot measured59.4%Only Qwen3.8 27B measured
LiveBench browserNot measured32.0%Only Qwen3.8 27B measured
LiveBench long agenticNot measured27.9%Only Qwen3.8 27B measured
Finance Agent (Vals AI)Not measured48.5%Only Qwen3.8 27B measured
Tax Agent Bench (Vals AI)Not measured30.9%Only Qwen3.8 27B measured
Legal Research Bench (Vals AI)Not measured36.1%Only Qwen3.8 27B measured
Excel Modeling Benchmark (Vals AI)Not measured59.7%Only Qwen3.8 27B measured
Terminal-Bench-Science (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
τ²-Bench Telecom86.8%Not measuredOnly MiniMax M2 measured
APEX-AgentsNot measured47.5%Only Qwen3.8 27B measured
Vending-Bench 2$161Not measuredOnly MiniMax M2 measured
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
GPQA DiamondNot measured88.9%Only Qwen3.8 27B measured
LiveBench reasoningNot measured80.0%Only Qwen3.8 27B measured
MMMU Pro (Vals AI)Not measured83.9%Only Qwen3.8 27B measured
GPQA Diamond (Artificial Analysis run)77.7%90.5%Qwen3.8 27B
Humanity's Last Exam (Artificial Analysis run)13.7%33.9%Qwen3.8 27B
ARC-AGINot measured87.5%Only Qwen3.8 27B measured
ARC-AGI-2Not measured42.4%Only Qwen3.8 27B measured
LMArena Text: hard prompts13571459Qwen3.8 27B
LMArena Text: expert13381479Qwen3.8 27B
LMArena Text: hard prompts in English13761461Qwen3.8 27B
LMArena Vision: diagramsNot measured1285Only Qwen3.8 27B measured
LMArena Vision: homeworkNot measured1295Only Qwen3.8 27B measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
AA Math Index78.3Not measuredOnly MiniMax M2 measured
AIME 2025 (Artificial Analysis run)78.3%Not measuredOnly MiniMax M2 measured
ProofBenchNot measured16.0%Only Qwen3.8 27B measured
LMArena Text: math13511455Qwen3.8 27B
LMArena Text: mathematical work13681458Qwen3.8 27B
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
MMLU ProNot measured84.3%Only Qwen3.8 27B measured
LegalBench (Vals AI)Not measured82.4%Only Qwen3.8 27B measured
TaxEval (Vals AI)Not measured70.8%Only Qwen3.8 27B measured
MortgageTax (Vals AI)Not measured64.9%Only Qwen3.8 27B measured
MedCode (Vals AI)Not measured28.7%Only Qwen3.8 27B measured
MMLU Pro (Artificial Analysis run)82.0%Not measuredOnly MiniMax M2 measured
LMArena Text: science13481467Qwen3.8 27B
LMArena Text: medicine and healthcare13671437Qwen3.8 27B
LMArena Text: legal and government13491447Qwen3.8 27B
LMArena Text: business and finance13361438Qwen3.8 27B
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
Design Arena: websites1144Not measuredOnly MiniMax M2 measured
Design Arena: UI components1136Not measuredOnly MiniMax M2 measured
Design Arena: game dev1119Not measuredOnly MiniMax M2 measured
Design Arena: data viz1140Not measuredOnly MiniMax M2 measured
Design Arena: 3D1098Not measuredOnly MiniMax M2 measured
Design Arena: all code categories1135Not measuredOnly MiniMax M2 measured
Design Arena: SVG1098Not measuredOnly MiniMax M2 measured
LiveBench designNot measured75.9%Only Qwen3.8 27B measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index016
General benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
LiveBench data analysisNot measured76.6%Only Qwen3.8 27B measured
SAGE (Vals AI)Not measured52.4%Only Qwen3.8 27B measured
MedScribe (Vals AI)Not measured83.8%Only Qwen3.8 27B measured
IFBench72.3%Not measuredOnly MiniMax M2 measured
Long context reasoning (AA-LCR)64.3%82.0%Qwen3.8 27B
DTBenchNot measured88.0%Only Qwen3.8 27B measured
LMCANot measured41.4%Only Qwen3.8 27B measured
Surface Evolver BenchNot measured45.0%Only Qwen3.8 27B measured
LMArena Text13401440Qwen3.8 27B
LMArena Text: instruction following13291436Qwen3.8 27B
LMArena Text: creative writing12861383Qwen3.8 27B
LMArena VisionNot measured1269Only Qwen3.8 27B measured
LMArena Text: English13641448Qwen3.8 27B
LMArena Text: non-English13131428Qwen3.8 27B
LMArena Text: Chinese13661501Qwen3.8 27B
LMArena Text: German13571443Qwen3.8 27B
LMArena Text: JapaneseNot measured1387Only Qwen3.8 27B measured
LMArena Text: KoreanNot measured1384Only Qwen3.8 27B measured
LMArena Text: French13361465Qwen3.8 27B
LMArena Text: Spanish13261449Qwen3.8 27B
LMArena Text: Russian13301415Qwen3.8 27B
LMArena Text: Polish13121439Qwen3.8 27B
LMArena Text: multi-turn13611440Qwen3.8 27B
LMArena Text: longer queries13311448Qwen3.8 27B
LMArena Text: writing and language12951405Qwen3.8 27B
LMArena Text: entertainment and media12981393Qwen3.8 27B
LMArena Vision: EnglishNot measured1267Only Qwen3.8 27B measured
LMArena Vision: ChineseNot measured1326Only Qwen3.8 27B measured
LMArena Vision: reading textNot measured1281Only Qwen3.8 27B measured
LMArena Vision: humorNot measured1235Only Qwen3.8 27B measured
LMArena Vision: creative writingNot measured1237Only Qwen3.8 27B measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for MiniMax M2 and Qwen3.8 27B
BenchmarkMiniMax M2Qwen3.8 27BLeader
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$0.0008Fits in one request
Qwen3.8 27B$0.0007Fits in one request

Qwen3.8 27B costs less

Repository review

50K input + 3K output tokens

MiniMax M2$0.016Fits in one request
Qwen3.8 27B$0.0060Fits in one request

Qwen3.8 27B costs less

Agent loop

200K input + 10K output tokens

MiniMax M2$0.061Exceeds the context window
Qwen3.8 27B$0.021Fits in one request

Qwen3.8 27B 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 and Qwen3.8 27B
SpecificationMiniMax M2Qwen3.8 27B
MakerMiniMaxQwen
WeightsOpen weightsOpen weights
ReleasedOctober 23, 2025August 14, 2026
Context window205K1M
Input $/Mtok$0.255$0.04
Output $/Mtok$1.02$1.35
Coding index45.373.6
Independent measurements behind it22
Cost per solved task$0.702$1.26
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2 better than Qwen3.8 27B for coding?

Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 45.3 for MiniMax M2. Pick MiniMax M2 when output tokens cost 1.3x less, or when a solved task costs $0.702 against $1.26.

Which is cheaper, MiniMax M2 or Qwen3.8 27B?

MiniMax M2 costs $0.255 per million input tokens and $1.02 per million output tokens; Qwen3.8 27B costs $0.04 and $1.35. Per solved SWE-bench Verified task, MiniMax M2 costs $0.702 and Qwen3.8 27B $1.26.

Which has the bigger context window, MiniMax M2 or Qwen3.8 27B?

Qwen3.8 27B, with 1M tokens against 205K.

How many benchmarks is the MiniMax M2 vs Qwen3.8 27B comparison based on?

32 benchmarks have a result for both models as of October 21, 2026. MiniMax M2's coding index rests on 2 independent benchmarks and Qwen3.8 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.

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