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MiniMax M2.7 vs Mistral Large 3 2512

MiniMax M2.7 leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 22.8 to 9.3, and MiniMax M2.7 costs 1.3x less per output token ($1.20 vs $1.50 per million). Updated October 22, 2026; 21 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Mistral Large 3 2512
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
19
Mistral Large 3 2512Mistral AI
Coding
No data
Overall
No data
Output $/M
$1.50
2
vs boards won of 21 shared

MiniMax M2.7 or Mistral Large 3 2512: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding.

Pick Mistral Large 3 2512 for a larger context window (262K against 205K tokens) and work measured by CaseLaw (Vals AI) or TaxEval (Vals AI), where it leads.

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BMistral Large 3 2512Mistral AINot benchmarked1 independent benchmark$0.77 per solved task
Shared results
21
MiniMax M2.7 only
53
Mistral Large 3 2512 only
7
Like-for-like categories
7 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 Large 3 2512 not benchmarked.
Widest category
Math, 48.1 points apart on average over 1 shared benchmark.
Widest single gap
AIME: MiniMax M2.7 91.0% against Mistral Large 3 2512 42.9%, 48.1 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Mistral Large 3 2512 $1.50 per million output tokens, 1.3x apart.
Context window
MiniMax M2.7 takes 205K tokens, Mistral Large 3 2512 262K.

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 Large 3 2512Ties
Coding40
Intelligence10
Agentic work10
Reasoning10
Math10
Knowledge32
Web design80
All shared boards192
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for MiniMax M2.7 and Mistral Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
LMArena WebDev1399Not measuredOnly MiniMax M2.7 measured
AA Coding Index52.620.1MiniMax M2.7
LiveCodeBench (Vals AI)79.9%55.3%MiniMax M2.7
SWE-bench Verified (Vals AI)73.8%41.4%MiniMax M2.7
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-Bench599.3264.7MiniMax M2.7
LMArena Text: coding1454Not measuredOnly MiniMax M2.7 measured
LMArena Text: software and IT1446Not measuredOnly MiniMax M2.7 measured
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 Mistral Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
AA Intelligence Index22.89.3MiniMax 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 Mistral Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
AA Agentic Index15.31.0MiniMax 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
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for MiniMax M2.7 and Mistral Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
GPQA Diamond86.6%68.4%MiniMax M2.7
MMMU Pro (Vals AI)Not measured66.2%Only Mistral Large 3 2512 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 prompts1422Not measuredOnly MiniMax M2.7 measured
LMArena Text: expert1443Not measuredOnly MiniMax M2.7 measured
LMArena Text: hard prompts in English1441Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for MiniMax M2.7 and Mistral Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
AIME91.0%42.9%MiniMax M2.7
MGSM (Vals AI)Not measured85.4%Only Mistral Large 3 2512 measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math1421Not measuredOnly MiniMax M2.7 measured
LMArena Text: mathematical work1437Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index32
Knowledge benchmarks for MiniMax M2.7 and Mistral Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
MMLU Pro80.4%79.8%MiniMax M2.7
LegalBench (Vals AI)84.0%79.1%MiniMax M2.7
CaseLaw (Vals AI)60.9%61.4%Mistral Large 3 2512
CorpFin (Vals AI)61.2%61.0%MiniMax M2.7
TaxEval (Vals AI)66.6%73.1%Mistral Large 3 2512
MortgageTax (Vals AI)Not measured52.1%Only Mistral Large 3 2512 measured
MedQA (Vals AI)Not measured82.2%Only Mistral Large 3 2512 measured
MedCode (Vals AI)34.4%Not measuredOnly MiniMax M2.7 measured
LMArena Text: science1416Not measuredOnly MiniMax M2.7 measured
LMArena Text: medicine and healthcare1409Not measuredOnly MiniMax M2.7 measured
LMArena Text: legal and government1403Not measuredOnly MiniMax M2.7 measured
LMArena Text: business and finance1407Not measuredOnly 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 index80
Web design benchmarks for MiniMax M2.7 and Mistral Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
Design Arena: websites12421162MiniMax M2.7
Design Arena: UI components12071099MiniMax M2.7
Design Arena: game dev12091079MiniMax M2.7
Design Arena: data viz12331137MiniMax M2.7
Design Arena: 3D11941099MiniMax M2.7
Design Arena: all code categories12331141MiniMax M2.7
Design Arena: SVG1137992MiniMax M2.7
Design Arena: ASCII art11361069MiniMax M2.7
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index24 boards, none shared
General benchmarks for MiniMax M2.7 and Mistral Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
SAGE (Vals AI)Not measured24.6%Only Mistral Large 3 2512 measured
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 measured65.1%Only Mistral Large 3 2512 measured
LMCANot measured16.7%Only Mistral Large 3 2512 measured
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text1405Not measuredOnly MiniMax M2.7 measured
LMArena Text: instruction following1405Not measuredOnly MiniMax M2.7 measured
LMArena Text: creative writing1354Not measuredOnly MiniMax M2.7 measured
LMArena Text: English1426Not measuredOnly MiniMax M2.7 measured
LMArena Text: non-English1382Not measuredOnly MiniMax M2.7 measured
LMArena Text: Chinese1442Not measuredOnly MiniMax M2.7 measured
LMArena Text: German1398Not measuredOnly MiniMax M2.7 measured
LMArena Text: Japanese1260Not measuredOnly MiniMax M2.7 measured
LMArena Text: Korean1314Not measuredOnly MiniMax M2.7 measured
LMArena Text: French1424Not measuredOnly MiniMax M2.7 measured
LMArena Text: Spanish1402Not measuredOnly MiniMax M2.7 measured
LMArena Text: Russian1383Not measuredOnly MiniMax M2.7 measured
LMArena Text: Polish1387Not measuredOnly MiniMax M2.7 measured
LMArena Text: multi-turn1412Not measuredOnly MiniMax M2.7 measured
LMArena Text: longer queries1418Not measuredOnly MiniMax M2.7 measured
LMArena Text: writing and language1376Not measuredOnly MiniMax M2.7 measured
LMArena Text: entertainment and media1360Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 24 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 Large 3 2512
BenchmarkMiniMax M2.7Mistral Large 3 2512Leader
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 Large 3 2512$0.0013Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Mistral Large 3 2512$0.029Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Mistral Large 3 2512$0.115Fits 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 Mistral Large 3 2512
SpecificationMiniMax M2.7Mistral Large 3 2512
MakerMiniMaxMistral AI
WeightsOpen weightsNo public weights listed
ReleasedMarch 18, 2026December 1, 2025
Context window205K262K
Input $/Mtok$0.30$0.50
Output $/Mtok$1.20$1.50
Coding index36.2Not benchmarked
Independent measurements behind it31
Cost per solved task$0.64$0.77
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than Mistral Large 3 2512 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for a larger context window (262K against 205K tokens) and work measured by CaseLaw (Vals AI) or TaxEval (Vals AI), where it leads.

Which is cheaper, MiniMax M2.7 or Mistral Large 3 2512?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Mistral Large 3 2512 costs $0.50 and $1.50. Per solved SWE-bench Verified task, MiniMax M2.7 costs $0.64 and Mistral Large 3 2512 $0.77.

Which has the bigger context window, MiniMax M2.7 or Mistral Large 3 2512?

Mistral Large 3 2512, with 262K tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs Mistral Large 3 2512 comparison based on?

21 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 Large 3 2512's on 1. Where only one model has a result, the page says so instead of naming a winner.

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