Enter opens the highlighted result. Esc closes.

MiniMax M2.7 vs Mistral Medium 3.1

MiniMax M2.7 leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 22.8 to 9.2, and MiniMax M2.7 costs 1.7x less per output token ($1.20 vs $2.00 per million). Updated October 22, 2026; 53 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Mistral Medium 3.1
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
32
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
21
vs boards won of 53 shared

MiniMax M2.7 or Mistral Medium 3.1: which to pick

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

Pick Mistral Medium 3.1 for work measured by LMArena Text: hard prompts or TaxEval (Vals AI), where it leads.

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
53
MiniMax M2.7 only
21
Mistral Medium 3.1 only
21
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 M2.7 36.2 from 3 benchmarks, Mistral Medium 3.1 not benchmarked.
Widest category
Agentic work, 28.8 points apart on average over 2 shared benchmarks.
Widest single gap
AIME: MiniMax M2.7 91.0% against Mistral Medium 3.1 42.3%, 48.8 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Mistral Medium 3.1 $2.00 per million output tokens, 1.7x apart.
Context window
MiniMax M2.7 takes 205K tokens, Mistral Medium 3.1 131K.

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 Medium 3.1Ties
Coding70
Intelligence10
Agentic work20
Reasoning41
Math30
Knowledge35
Web design80
General415
All shared boards3221
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for MiniMax M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
LMArena WebDev1399Not measuredOnly MiniMax M2.7 measured
AA Coding Index52.620.5MiniMax M2.7
LiveCodeBench (Vals AI)79.9%44.8%MiniMax M2.7
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
LiveCodeBench (Artificial Analysis run)Not measured40.6%Only Mistral Medium 3.1 measured
SciCode50.1%32.4%MiniMax M2.7
Terminal-Bench Hard (Artificial Analysis run)39.4%10.6%MiniMax M2.7
Terminal-Bench45.1%Not measuredOnly MiniMax M2.7 measured
WeirdML37.0%Not measuredOnly MiniMax M2.7 measured
ALE-Bench599.3210.2MiniMax M2.7
LMArena Text: coding14541433MiniMax M2.7
LMArena Text: software and IT14461436MiniMax 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 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for MiniMax M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
AA Intelligence Index22.89.2MiniMax M2.7
Epoch Capabilities Index145.8Not measuredOnly MiniMax M2.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for MiniMax M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
AA Agentic Index15.31.9MiniMax 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%40.6%MiniMax M2.7
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
Reasoning benchmarks for MiniMax M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
GPQA Diamond86.6%Not measuredOnly MiniMax M2.7 measured
MMMU Pro (Vals AI)Not measured63.0%Only Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)87.4%58.8%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)29.6%4.7%MiniMax M2.7
LMArena Text: hard prompts14221426Mistral Medium 3.1
LMArena Text: expert14431408MiniMax M2.7
LMArena Text: hard prompts in English14411435MiniMax M2.7
LMArena Vision: diagramsNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: homeworkNot measured1165Only Mistral Medium 3.1 measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for MiniMax M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
AIME91.0%42.3%MiniMax M2.7
MATH 500 (Vals AI)Not measured87.0%Only Mistral Medium 3.1 measured
MGSM (Vals AI)Not measured90.9%Only Mistral Medium 3.1 measured
AA Math IndexNot measured38.3Only Mistral Medium 3.1 measured
AIME 2025 (Artificial Analysis run)Not measured38.3%Only Mistral Medium 3.1 measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math14211408MiniMax M2.7
LMArena Text: mathematical work14371412MiniMax M2.7
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index35
Knowledge benchmarks for MiniMax M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
MMLU Pro80.4%75.3%MiniMax M2.7
LegalBench (Vals AI)84.0%62.0%MiniMax M2.7
CaseLaw (Vals AI)60.9%Not measuredOnly MiniMax M2.7 measured
CorpFin (Vals AI)61.2%50.7%MiniMax M2.7
TaxEval (Vals AI)66.6%70.3%Mistral Medium 3.1
MortgageTax (Vals AI)Not measured36.5%Only Mistral Medium 3.1 measured
MedQA (Vals AI)Not measured78.2%Only Mistral Medium 3.1 measured
MedCode (Vals AI)34.4%Not measuredOnly MiniMax M2.7 measured
MMLU Pro (Artificial Analysis run)Not measured68.3%Only Mistral Medium 3.1 measured
LMArena Text: science14161444Mistral Medium 3.1
LMArena Text: medicine and healthcare14091449Mistral Medium 3.1
LMArena Text: legal and government14031439Mistral Medium 3.1
LMArena Text: business and finance14071418Mistral Medium 3.1
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for MiniMax M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
Design Arena: websites12431132MiniMax M2.7
Design Arena: UI components12101097MiniMax M2.7
Design Arena: game dev12091073MiniMax M2.7
Design Arena: data viz12331144MiniMax M2.7
Design Arena: 3D11951081MiniMax M2.7
Design Arena: all code categories12331120MiniMax M2.7
Design Arena: SVG1137992MiniMax M2.7
Design Arena: ASCII art1136997MiniMax M2.7
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index415
General benchmarks for MiniMax M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
MedScribe (Vals AI)79.9%Not measuredOnly MiniMax M2.7 measured
IFBench75.7%39.8%MiniMax M2.7
Long context reasoning (AA-LCR)78.3%42.7%MiniMax M2.7
DTBenchNot measured67.5%Only Mistral Medium 3.1 measured
LMCANot measured19.1%Only Mistral Medium 3.1 measured
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text14051424Mistral Medium 3.1
LMArena Text: instruction following14051398MiniMax M2.7
LMArena Text: creative writing13541391Mistral Medium 3.1
LMArena VisionNot measured1172Only Mistral Medium 3.1 measured
LMArena Text: English14261438Mistral Medium 3.1
LMArena Text: non-English13821408Mistral Medium 3.1
LMArena Text: Chinese14421447Mistral Medium 3.1
LMArena Text: German13981432Mistral Medium 3.1
LMArena Text: Japanese12601379Mistral Medium 3.1
LMArena Text: Korean13141380Mistral Medium 3.1
LMArena Text: French14241460Mistral Medium 3.1
LMArena Text: Spanish14021433Mistral Medium 3.1
LMArena Text: Russian13831411Mistral Medium 3.1
LMArena Text: Polish13871430Mistral Medium 3.1
LMArena Text: multi-turn14121418Mistral Medium 3.1
LMArena Text: longer queries14181406MiniMax M2.7
LMArena Text: writing and language13761395Mistral Medium 3.1
LMArena Text: entertainment and media13601390Mistral Medium 3.1
LMArena Vision: EnglishNot measured1179Only Mistral Medium 3.1 measured
LMArena Vision: ChineseNot measured1190Only Mistral Medium 3.1 measured
LMArena Vision: reading textNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: humorNot measured1168Only Mistral Medium 3.1 measured
LMArena Vision: captioningNot measured1145Only Mistral Medium 3.1 measured
LMArena Vision: recognizing thingsNot measured1147Only Mistral Medium 3.1 measured
LMArena Vision: creative writingNot measured1200Only Mistral Medium 3.1 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 M2.7 and Mistral Medium 3.1
BenchmarkMiniMax M2.7Mistral Medium 3.1Leader
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 Medium 3.1$0.0014Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Mistral Medium 3.1$0.026Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Mistral Medium 3.1$0.100Exceeds 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 Medium 3.1
SpecificationMiniMax M2.7Mistral Medium 3.1
MakerMiniMaxMistral AI
WeightsOpen weightsNo public weights listed
ReleasedMarch 18, 2026August 13, 2025
Context window205K131K
Input $/Mtok$0.30$0.40
Output $/Mtok$1.20$2.00
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 Medium 3.1 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding. Pick Mistral Medium 3.1 for work measured by LMArena Text: hard prompts or TaxEval (Vals AI), where it leads.

Which is cheaper, MiniMax M2.7 or Mistral Medium 3.1?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Mistral Medium 3.1 costs $0.40 and $2.00. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Mistral Medium 3.1?

MiniMax M2.7, with 205K tokens against 131K.

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

53 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 Medium 3.1's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next