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MiniMax M2.1 vs MiniMax M2.7

MiniMax M2.7 leads MiniMax M2.1 on the Artificial Analysis Intelligence Index, 22.8 to 20.9, at about the same output price ($1.20 vs $1.20 per million). Updated October 22, 2026; 27 benchmarks have a result for both.

Replace MiniMax M2.1 Replace MiniMax M2.7
MiniMax M2.1MiniMax
Coding
No data
Overall
No data
Output $/M
$1.20
7
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
20
vs boards won of 27 shared

MiniMax M2.1 or MiniMax M2.7: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding.

Pick MiniMax M2.1 for a lower cost per solved task ($0.59 against $0.64) and work measured by LiveCodeBench (Vals AI) or SWE-bench Verified (Vals AI), where it leads.

Model AMiniMax M2.1MiniMaxNot benchmarked1 independent benchmark$0.59 per solved taskModel BMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved task
Shared results
27
MiniMax M2.1 only
7
MiniMax M2.7 only
47
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, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
Math, 13.1 points apart on average over 1 shared benchmark.
Widest single gap
AIME: MiniMax M2.1 77.9% against MiniMax M2.7 91.0%, 13.1 points apart on a 0 to 100 scale.
Output price
Both cost $1.20 per million output tokens.
Context window
Both take 205K tokens.

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 M2.1BarsMiniMax M2.7Ties
Coding32
Intelligence01
Agentic work10
Reasoning03
Math01
Knowledge15
Web design16
General12
All shared boards720
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
Coding benchmarks for MiniMax M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
LMArena WebDevNot measured1399Only MiniMax M2.7 measured
AA Coding IndexNot measured52.6Only MiniMax M2.7 measured
LiveCodeBench (Vals AI)81.8%79.9%MiniMax M2.1
SWE-bench Verified (Vals AI)74.8%73.8%MiniMax M2.1
Vibe Code Bench (Vals AI)Not measured11.9%Only MiniMax M2.7 measured
Code migration (Vals AI)Not measured8.7%Only MiniMax M2.7 measured
ProgramBench (Vals AI)Not measured0.0%Only MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)Not measured48.7%Only MiniMax M2.7 measured
LiveCodeBench (Artificial Analysis run)81.0%Not measuredOnly MiniMax M2.1 measured
SciCodeNot measured50.1%Only MiniMax M2.7 measured
Terminal-Bench Hard (Artificial Analysis run)28.8%39.4%MiniMax M2.7
Terminal-Bench36.6%45.1%MiniMax M2.7
WeirdMLNot measured37.0%Only MiniMax M2.7 measured
ALE-Bench623.8599.3MiniMax M2.1
LMArena Text: codingNot measured1454Only MiniMax M2.7 measured
LMArena Text: software and ITNot measured1446Only MiniMax M2.7 measured
LMArena WebDev: ReactNot measured1388Only MiniMax M2.7 measured
LMArena WebDev: HTMLNot measured1401Only MiniMax M2.7 measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for MiniMax M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
AA Intelligence Index20.922.8MiniMax M2.7
Epoch Capabilities IndexNot measured145.8Only MiniMax M2.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for MiniMax M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
AA Agentic IndexNot measured15.3Only MiniMax M2.7 measured
Finance Agent (Vals AI)Not measured27.9%Only MiniMax M2.7 measured
Tax Agent Bench (Vals AI)Not measured6.9%Only MiniMax M2.7 measured
Legal Research Bench (Vals AI)Not measured10.6%Only MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)Not measured28.4%Only MiniMax M2.7 measured
τ²-Bench Telecom85.4%84.8%MiniMax M2.1
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for MiniMax M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
GPQA Diamond78.5%86.6%MiniMax M2.7
GPQA Diamond (Artificial Analysis run)83.0%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)23.2%29.6%MiniMax M2.7
LMArena Text: hard promptsNot measured1422Only MiniMax M2.7 measured
LMArena Text: expertNot measured1443Only MiniMax M2.7 measured
LMArena Text: hard prompts in EnglishNot measured1441Only MiniMax M2.7 measured
Neither model has a result on the other 17 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for MiniMax M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
AIME77.9%91.0%MiniMax M2.7
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 Index82.7Not measuredOnly MiniMax M2.1 measured
AIME 2025 (Artificial Analysis run)82.7%Not measuredOnly MiniMax M2.1 measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
LMArena Text: mathNot measured1421Only MiniMax M2.7 measured
LMArena Text: mathematical workNot measured1437Only MiniMax M2.7 measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
Knowledge benchmarks for MiniMax M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
MMLU Pro87.0%80.4%MiniMax M2.1
LegalBench (Vals AI)75.5%84.0%MiniMax M2.7
CaseLaw (Vals AI)55.8%60.9%MiniMax M2.7
CorpFin (Vals AI)58.9%61.2%MiniMax M2.7
TaxEval (Vals AI)66.3%66.6%MiniMax M2.7
MedQA (Vals AI)91.2%Not measuredOnly MiniMax M2.1 measured
MedCode (Vals AI)34.1%34.4%MiniMax M2.7
MMLU Pro (Artificial Analysis run)87.5%Not measuredOnly MiniMax M2.1 measured
LMArena Text: scienceNot measured1416Only MiniMax M2.7 measured
LMArena Text: medicine and healthcareNot measured1409Only MiniMax M2.7 measured
LMArena Text: legal and governmentNot measured1403Only MiniMax M2.7 measured
LMArena Text: business and financeNot measured1407Only MiniMax M2.7 measured
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index16
Web design benchmarks for MiniMax M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
Design Arena: websites12011242MiniMax M2.7
Design Arena: UI components12201207MiniMax M2.1
Design Arena: game dev11341209MiniMax M2.7
Design Arena: data viz12061233MiniMax M2.7
Design Arena: 3D11641194MiniMax M2.7
Design Arena: all code categories11901233MiniMax M2.7
Design Arena: SVG11311137MiniMax M2.7
Design Arena: ASCII artNot measured1136Only 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 index12
General benchmarks for MiniMax M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
MedScribe (Vals AI)80.8%79.9%MiniMax M2.1
IFBench69.9%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)67.7%78.3%MiniMax M2.7
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena TextNot measured1405Only MiniMax M2.7 measured
LMArena Text: instruction followingNot measured1405Only MiniMax M2.7 measured
LMArena Text: creative writingNot measured1354Only MiniMax M2.7 measured
LMArena Text: EnglishNot measured1426Only MiniMax M2.7 measured
LMArena Text: non-EnglishNot measured1382Only MiniMax M2.7 measured
LMArena Text: ChineseNot measured1442Only MiniMax M2.7 measured
LMArena Text: GermanNot measured1398Only MiniMax M2.7 measured
LMArena Text: JapaneseNot measured1260Only MiniMax M2.7 measured
LMArena Text: KoreanNot measured1314Only MiniMax M2.7 measured
LMArena Text: FrenchNot measured1424Only MiniMax M2.7 measured
LMArena Text: SpanishNot measured1402Only MiniMax M2.7 measured
LMArena Text: RussianNot measured1383Only MiniMax M2.7 measured
LMArena Text: PolishNot measured1387Only MiniMax M2.7 measured
LMArena Text: multi-turnNot measured1412Only MiniMax M2.7 measured
LMArena Text: longer queriesNot measured1418Only MiniMax M2.7 measured
LMArena Text: writing and languageNot measured1376Only MiniMax M2.7 measured
LMArena Text: entertainment and mediaNot measured1360Only 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 M2.1 and MiniMax M2.7
BenchmarkMiniMax M2.1MiniMax M2.7Leader
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
MiniMax M2.7$0.0009Fits in one request

Same cost

Repository review

50K input + 3K output tokens

MiniMax M2.1$0.019Fits in one request
MiniMax M2.7$0.019Fits in one request

Same cost

Agent loop

200K input + 10K output tokens

MiniMax M2.1$0.072Exceeds the context window
MiniMax M2.7$0.072Exceeds the context window

Same cost

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 MiniMax M2.7
SpecificationMiniMax M2.1MiniMax M2.7
MakerMiniMaxMiniMax
WeightsOpen weightsOpen weights
ReleasedDecember 23, 2025March 18, 2026
Context window205K205K
Input $/Mtok$0.30$0.30
Output $/Mtok$1.20$1.20
Coding indexNot benchmarked36.2
Independent measurements behind it13
Cost per solved task$0.59$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.1 better than MiniMax M2.7 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; MiniMax M2.1 has none, so the two cannot be ranked on coding. Pick MiniMax M2.1 for a lower cost per solved task ($0.59 against $0.64) and work measured by LiveCodeBench (Vals AI) or SWE-bench Verified (Vals AI), where it leads.

Which is cheaper, MiniMax M2.1 or MiniMax M2.7?

MiniMax M2.1 costs $0.30 per million input tokens and $1.20 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Per solved SWE-bench Verified task, MiniMax M2.1 costs $0.59 and MiniMax M2.7 $0.64.

Which has the bigger context window, MiniMax M2.1 or MiniMax M2.7?

Neither: both take 205K tokens.

How many benchmarks is the MiniMax M2.1 vs MiniMax M2.7 comparison based on?

27 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.1's coding index rests on 1 independent benchmark and MiniMax M2.7's on 3. Where only one model has a result, the page says so instead of naming a winner.

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