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MiniMax M2.7 vs Mistral Small 3.1 24B

Mistral Small 3.1 24B costs 2.2x less per output token than MiniMax M2.7 ($0.555 vs $1.20 per million). Updated October 22, 2026; 28 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Mistral Small 3.1 24B
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
28
Mistral Small 3.1 24BMistral AI
Coding
No data
Overall
No data
Output $/M
$0.555
0
vs boards won of 28 shared

MiniMax M2.7 or Mistral Small 3.1 24B: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Mistral Small 3.1 24B has none, so the two cannot be ranked on coding.

Pick Mistral Small 3.1 24B for output tokens 2.2x cheaper ($0.555 vs $1.20 per million).

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BMistral Small 3.1 24BMistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
28
MiniMax M2.7 only
46
Mistral Small 3.1 24B only
10
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.

At a glance

Coding index
MiniMax M2.7 36.2 from 3 benchmarks, Mistral Small 3.1 24B not benchmarked.
Widest category
Math, 27.1 points apart on average over 2 shared benchmarks.
Widest single gap
LMArena Text: Chinese: MiniMax M2.7 1442 against Mistral Small 3.1 24B 1253, 31.5 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Mistral Small 3.1 24B $0.555 per million output tokens, 2.2x apart.
Context window
MiniMax M2.7 takes 205K tokens, Mistral Small 3.1 24B 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 M2.7BarsMistral Small 3.1 24BTies
Coding20
Reasoning30
Math20
Knowledge40
General170
All shared boards280
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for MiniMax M2.7 and Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
LMArena WebDev1399Not measuredOnly MiniMax M2.7 measured
AA Coding Index52.6Not measuredOnly MiniMax M2.7 measured
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%Not measuredOnly MiniMax M2.7 measured
ALE-Bench599.3Not measuredOnly MiniMax M2.7 measured
LMArena Text: coding14541309MiniMax M2.7
LMArena Text: software and IT14461301MiniMax 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
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for MiniMax M2.7 and Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
AA Intelligence Index22.8Not measuredOnly MiniMax M2.7 measured
Epoch Capabilities Index145.8Not measuredOnly MiniMax M2.7 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Agentic work benchmarks for MiniMax M2.7 and Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
AA Agentic Index15.3Not measuredOnly MiniMax M2.7 measured
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
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for MiniMax M2.7 and Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
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
LMArena Text: hard prompts14221278MiniMax M2.7
LMArena Text: expert14431257MiniMax M2.7
LMArena Text: hard prompts in English14411290MiniMax M2.7
LMArena Vision: diagramsNot measured1119Only Mistral Small 3.1 24B measured
LMArena Vision: homeworkNot measured1158Only Mistral Small 3.1 24B measured
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 Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
AIME91.0%Not measuredOnly MiniMax M2.7 measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math14211261MiniMax M2.7
LMArena Text: mathematical work14371271MiniMax M2.7
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for MiniMax M2.7 and Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
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
LMArena Text: science14161265MiniMax M2.7
LMArena Text: medicine and healthcare14091267MiniMax M2.7
LMArena Text: legal and government14031271MiniMax M2.7
LMArena Text: business and finance14071257MiniMax M2.7
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 Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
Design Arena: websites1242Not measuredOnly MiniMax M2.7 measured
Design Arena: UI components1207Not measuredOnly MiniMax M2.7 measured
Design Arena: game dev1209Not measuredOnly MiniMax M2.7 measured
Design Arena: data viz1233Not measuredOnly MiniMax M2.7 measured
Design Arena: 3D1194Not measuredOnly MiniMax M2.7 measured
Design Arena: all code categories1233Not measuredOnly MiniMax M2.7 measured
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 index170
General benchmarks for MiniMax M2.7 and Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
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
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text14051277MiniMax M2.7
LMArena Text: instruction following14051263MiniMax M2.7
LMArena Text: creative writing13541252MiniMax M2.7
LMArena VisionNot measured1136Only Mistral Small 3.1 24B measured
LMArena Text: English14261295MiniMax M2.7
LMArena Text: non-English13821255MiniMax M2.7
LMArena Text: Chinese14421253MiniMax M2.7
LMArena Text: German13981266MiniMax M2.7
LMArena Text: Japanese12601208MiniMax M2.7
LMArena Text: Korean13141207MiniMax M2.7
LMArena Text: French14241273MiniMax M2.7
LMArena Text: Spanish14021284MiniMax M2.7
LMArena Text: Russian13831263MiniMax M2.7
LMArena Text: Polish13871242MiniMax M2.7
LMArena Text: multi-turn14121270MiniMax M2.7
LMArena Text: longer queries14181299MiniMax M2.7
LMArena Text: writing and language13761268MiniMax M2.7
LMArena Text: entertainment and media13601250MiniMax M2.7
LMArena Vision: EnglishNot measured1157Only Mistral Small 3.1 24B measured
LMArena Vision: ChineseNot measured1155Only Mistral Small 3.1 24B measured
LMArena Vision: reading textNot measured1132Only Mistral Small 3.1 24B measured
LMArena Vision: humorNot measured1142Only Mistral Small 3.1 24B measured
LMArena Vision: captioningNot measured1153Only Mistral Small 3.1 24B measured
LMArena Vision: recognizing thingsNot measured1155Only Mistral Small 3.1 24B measured
LMArena Vision: creative writingNot measured1123Only Mistral Small 3.1 24B measured
Neither model has a result on the other 19 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 Mistral Small 3.1 24B
BenchmarkMiniMax M2.7Mistral Small 3.1 24BLeader
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
Mistral Small 3.1 24B$0.0006Fits in one request

Mistral Small 3.1 24B costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Mistral Small 3.1 24B$0.019Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Mistral Small 3.1 24B$0.076Exceeds 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 Mistral Small 3.1 24B
SpecificationMiniMax M2.7Mistral Small 3.1 24B
MakerMiniMaxMistral AI
WeightsOpen weightsOpen weights
ReleasedMarch 18, 2026March 17, 2025
Context window205K128K
Input $/Mtok$0.30$0.351
Output $/Mtok$1.20$0.555
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 Mistral Small 3.1 24B for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Mistral Small 3.1 24B has none, so the two cannot be ranked on coding. Pick Mistral Small 3.1 24B for output tokens 2.2x cheaper ($0.555 vs $1.20 per million).

Which is cheaper, MiniMax M2.7 or Mistral Small 3.1 24B?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Mistral Small 3.1 24B costs $0.351 and $0.555. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Mistral Small 3.1 24B?

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

How many benchmarks is the MiniMax M2.7 vs Mistral Small 3.1 24B comparison based on?

28 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.7's coding index rests on 3 independent benchmarks and Mistral Small 3.1 24B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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