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MiniMax M2.7 vs MiMo-V2.5

MiMo-V2.5 leads MiniMax M2.7 on coding, 50.0 to 36.2 on the Vibe Coding Index, and MiMo-V2.5 costs 3.6x less per output token ($0.336 vs $1.20 per million). Updated October 22, 2026; 67 benchmarks have a result for both.

Replace MiniMax M2.7 Replace MiMo-V2.5
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
14
MiMo-V2.5Xiaomi
Coding
50.0
Overall
50.7
Output $/M
$0.336
53
vs boards won of 67 shared

MiniMax M2.7 or MiMo-V2.5: which to pick

Pick MiMo-V2.5 for coding: it scores 50.0 on the Vibe Coding Index against 36.2 for MiniMax M2.7.

Pick MiniMax M2.7 for work measured by SWE-bench Verified (Vals AI) or SciCode, where it leads.

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BMiMo-V2.5Xiaomi50.0/1003 independent benchmarks$0.01 per solved task
Shared results
67
MiniMax M2.7 only
7
MiMo-V2.5 only
13
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, MiMo-V2.5 50.0 from 3 benchmarks.
Widest category
Agentic work, 7.4 points apart on average over 6 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): MiniMax M2.7 11.9% against MiMo-V2.5 42.2%, 30.2 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against MiMo-V2.5 $0.336 per million output tokens, 3.6x apart.
Context window
MiniMax M2.7 takes 205K tokens, MiMo-V2.5 1.05M.

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 M2.7BarsMiMo-V2.5Ties
Coding311
Intelligence10
Agentic work15
Reasoning33
Math03
Knowledge36
Web design08
General317
All shared boards1453
CodingLike-for-likeSix of these boards feed the Vibe Coding Index311
Coding benchmarks for MiniMax M2.7 and MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
LMArena WebDev13991438MiMo-V2.5
AA Coding Index52.656.8MiMo-V2.5
LiveCodeBench (Vals AI)79.9%81.5%MiMo-V2.5
SWE-bench Verified (Vals AI)73.8%71.0%MiniMax M2.7
Vibe Code Bench (Vals AI)11.9%42.2%MiMo-V2.5
Code migration (Vals AI)8.7%14.2%MiMo-V2.5
ProgramBench (Vals AI)0.0%Not measuredOnly MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)48.7%60.7%MiMo-V2.5
SciCode50.1%43.9%MiniMax M2.7
Terminal-Bench Hard (Artificial Analysis run)39.4%41.7%MiMo-V2.5
Terminal-Bench45.1%Not measuredOnly MiniMax M2.7 measured
WeirdML37.0%Not measuredOnly MiniMax M2.7 measured
ALE-Bench599.3514.0MiniMax M2.7
LMArena Text: coding14541469MiMo-V2.5
LMArena Text: software and IT14461463MiMo-V2.5
LMArena WebDev: React13881425MiMo-V2.5
LMArena WebDev: HTML14011429MiMo-V2.5
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for MiniMax M2.7 and MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
AA Intelligence Index22.821.8MiniMax M2.7
Epoch Capabilities Index145.8Not measuredOnly MiniMax M2.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index15
Agentic work benchmarks for MiniMax M2.7 and MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
AA Agentic Index15.315.8MiMo-V2.5
Finance Agent (Vals AI)27.9%36.7%MiMo-V2.5
Tax Agent Bench (Vals AI)6.9%7.8%MiMo-V2.5
Legal Research Bench (Vals AI)10.6%9.1%MiniMax M2.7
Excel Modeling Benchmark (Vals AI)28.4%55.1%MiMo-V2.5
τ²-Bench Telecom84.8%90.6%MiMo-V2.5
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
Reasoning benchmarks for MiniMax M2.7 and MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
GPQA Diamond86.6%81.6%MiniMax M2.7
MMMU Pro (Vals AI)Not measured80.0%Only MiMo-V2.5 measured
GPQA Diamond (Artificial Analysis run)87.4%84.9%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)29.6%27.2%MiniMax M2.7
LMArena Text: hard prompts14221450MiMo-V2.5
LMArena Text: expert14431459MiMo-V2.5
LMArena Text: hard prompts in English14411461MiMo-V2.5
LMArena Vision: diagramsNot measured1269Only MiMo-V2.5 measured
LMArena Vision: homeworkNot measured1262Only MiMo-V2.5 measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for MiniMax M2.7 and MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
AIME91.0%Not measuredOnly MiniMax M2.7 measured
ProofBench3.0%16.0%MiMo-V2.5
LMArena Text: math14211436MiMo-V2.5
LMArena Text: mathematical work14371451MiMo-V2.5
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index36
Knowledge benchmarks for MiniMax M2.7 and MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
MMLU Pro80.4%82.9%MiMo-V2.5
LegalBench (Vals AI)84.0%78.9%MiniMax M2.7
CaseLaw (Vals AI)60.9%Not measuredOnly MiniMax M2.7 measured
CorpFin (Vals AI)61.2%59.9%MiniMax M2.7
TaxEval (Vals AI)66.6%71.8%MiMo-V2.5
MortgageTax (Vals AI)Not measured59.3%Only MiMo-V2.5 measured
MedCode (Vals AI)34.4%31.9%MiniMax M2.7
LMArena Text: science14161440MiMo-V2.5
LMArena Text: medicine and healthcare14091432MiMo-V2.5
LMArena Text: legal and government14031425MiMo-V2.5
LMArena Text: business and finance14071432MiMo-V2.5
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for MiniMax M2.7 and MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
Design Arena: websites12431265MiMo-V2.5
Design Arena: UI components12101255MiMo-V2.5
Design Arena: game dev12091249MiMo-V2.5
Design Arena: data viz12331250MiMo-V2.5
Design Arena: 3D11951215MiMo-V2.5
Design Arena: all code categories12331260MiMo-V2.5
Design Arena: SVG11371179MiMo-V2.5
Design Arena: ASCII art11361140MiMo-V2.5
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index317
General benchmarks for MiniMax M2.7 and MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
SAGE (Vals AI)Not measured43.3%Only MiMo-V2.5 measured
MedScribe (Vals AI)79.9%72.2%MiniMax M2.7
Vals Multimodal IndexNot measured52.8%Only MiMo-V2.5 measured
IFBench75.7%67.1%MiniMax M2.7
Long context reasoning (AA-LCR)78.3%73.0%MiniMax M2.7
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text14051428MiMo-V2.5
LMArena Text: instruction following14051435MiMo-V2.5
LMArena Text: creative writing13541393MiMo-V2.5
LMArena VisionNot measured1247Only MiMo-V2.5 measured
LMArena Text: English14261447MiMo-V2.5
LMArena Text: non-English13821405MiMo-V2.5
LMArena Text: Chinese14421469MiMo-V2.5
LMArena Text: German13981421MiMo-V2.5
LMArena Text: Japanese12601306MiMo-V2.5
LMArena Text: Korean13141361MiMo-V2.5
LMArena Text: French14241448MiMo-V2.5
LMArena Text: Spanish14021414MiMo-V2.5
LMArena Text: Russian13831396MiMo-V2.5
LMArena Text: Polish13871413MiMo-V2.5
LMArena Text: multi-turn14121445MiMo-V2.5
LMArena Text: longer queries14181445MiMo-V2.5
LMArena Text: writing and language13761409MiMo-V2.5
LMArena Text: entertainment and media13601399MiMo-V2.5
LMArena Vision: EnglishNot measured1259Only MiMo-V2.5 measured
LMArena Vision: ChineseNot measured1326Only MiMo-V2.5 measured
LMArena Vision: reading textNot measured1256Only MiMo-V2.5 measured
LMArena Vision: humorNot measured1226Only MiMo-V2.5 measured
LMArena Vision: recognizing thingsNot measured1189Only MiMo-V2.5 measured
LMArena Vision: creative writingNot measured1230Only MiMo-V2.5 measured
Neither model has a result on the other 16 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 MiMo-V2.5
BenchmarkMiniMax M2.7MiMo-V2.5Leader
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
MiMo-V2.5$0.0003Fits in one request

MiMo-V2.5 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
MiMo-V2.5$0.0094Fits in one request

MiMo-V2.5 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
MiMo-V2.5$0.037Fits in one request

MiMo-V2.5 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 MiMo-V2.5
SpecificationMiniMax M2.7Xiaomi MiMo-V2.5
MakerMiniMaxXiaomi
WeightsOpen weightsOpen weights
ReleasedMarch 18, 2026April 22, 2026
Context window205K1.05M
Input $/Mtok$0.30$0.168
Output $/Mtok$1.20$0.336
Coding index36.250.0
Independent measurements behind it33
Cost per solved task$0.64$0.01
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than MiMo-V2.5 for coding?

Pick MiMo-V2.5 for coding: it scores 50.0 on the Vibe Coding Index against 36.2 for MiniMax M2.7. Pick MiniMax M2.7 for work measured by SWE-bench Verified (Vals AI) or SciCode, where it leads.

Which is cheaper, MiniMax M2.7 or MiMo-V2.5?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; MiMo-V2.5 costs $0.168 and $0.336. Per solved SWE-bench Verified task, MiniMax M2.7 costs $0.64 and MiMo-V2.5 $0.01.

Which has the bigger context window, MiniMax M2.7 or MiMo-V2.5?

MiMo-V2.5, with 1.05M tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs MiMo-V2.5 comparison based on?

67 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.7's coding index rests on 3 independent benchmarks and MiMo-V2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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