Enter opens the highlighted result. Esc closes.

LongCat 2.0 vs MiniMax M2.7

MiniMax M2.7 leads LongCat 2.0 on the Artificial Analysis Intelligence Index, 22.8 to 19.1, at about the same output price ($1.20 vs $1.20 per million). Updated October 22, 2026; 8 benchmarks have a result for both.

LongCat 2.0Meituan
Coding
No data
Overall
No data
Output $/M
$1.20
2
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
6
vs boards won of 8 shared

LongCat 2.0 or MiniMax M2.7: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; LongCat 2.0 has none, so the two cannot be ranked on coding.

Pick LongCat 2.0 for a larger context window (1.05M against 205K tokens) and work measured by ALE-Bench or Humanity's Last Exam (Artificial Analysis run), where it leads.

Shared results
8
LongCat 2.0 only
0
MiniMax M2.7 only
66
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
LongCat 2.0 not benchmarked, MiniMax M2.7 36.2 from 3 benchmarks.
Widest category
General, 13.3 points apart on average over 1 shared benchmark.
Widest single gap
SciCode: LongCat 2.0 36.3% against MiniMax M2.7 50.1%, 13.8 points apart on a 0 to 100 scale.
Output price
Both cost $1.20 per million output tokens.
Context window
LongCat 2.0 takes 1.05M tokens, MiniMax M2.7 205K.

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
CategoryLongCat 2.0BarsMiniMax M2.7Ties
Coding12
Intelligence01
Agentic work01
Reasoning11
General01
All shared boards26
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
Coding benchmarks for LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax M2.7Leader
LMArena WebDevNot measured1399Only MiniMax M2.7 measured
AA Coding Index45.352.6MiniMax M2.7
LiveCodeBench (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
SWE-bench Verified (Vals AI)Not measured73.8%Only MiniMax M2.7 measured
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
SciCode36.3%50.1%MiniMax M2.7
Terminal-Bench Hard (Artificial Analysis run)Not measured39.4%Only MiniMax M2.7 measured
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
WeirdMLNot measured37.0%Only MiniMax M2.7 measured
ALE-Bench793.5599.3LongCat 2.0
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 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax M2.7Leader
AA Intelligence Index19.122.8MiniMax M2.7
Epoch Capabilities IndexNot measured145.8Only MiniMax M2.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax M2.7Leader
AA Agentic Index14.015.3MiniMax M2.7
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 TelecomNot measured84.8%Only 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 index11
Reasoning benchmarks for LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)78.0%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)33.7%29.6%LongCat 2.0
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
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 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 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Knowledge benchmarks for LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax M2.7Leader
MMLU ProNot measured80.4%Only MiniMax M2.7 measured
LegalBench (Vals AI)Not measured84.0%Only MiniMax M2.7 measured
CaseLaw (Vals AI)Not measured60.9%Only MiniMax M2.7 measured
CorpFin (Vals AI)Not measured61.2%Only MiniMax M2.7 measured
TaxEval (Vals AI)Not measured66.6%Only MiniMax M2.7 measured
MedCode (Vals AI)Not measured34.4%Only MiniMax M2.7 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 10 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax M2.7Leader
Design Arena: websitesNot measured1242Only MiniMax M2.7 measured
Design Arena: UI componentsNot measured1207Only MiniMax M2.7 measured
Design Arena: game devNot measured1209Only MiniMax M2.7 measured
Design Arena: data vizNot measured1233Only MiniMax M2.7 measured
Design Arena: 3DNot measured1194Only MiniMax M2.7 measured
Design Arena: all code categoriesNot measured1233Only MiniMax M2.7 measured
Design Arena: SVGNot measured1137Only MiniMax M2.7 measured
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 index01
General benchmarks for LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax M2.7Leader
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBenchNot measured75.7%Only MiniMax M2.7 measured
Long context reasoning (AA-LCR)65.0%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 LongCat 2.0 and MiniMax M2.7
BenchmarkLongCat 2.0MiniMax 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

LongCat 2.0$0.0009Fits in one request
MiniMax M2.7$0.0009Fits in one request

Same cost

Repository review

50K input + 3K output tokens

LongCat 2.0$0.019Fits in one request
MiniMax M2.7$0.019Fits in one request

Same cost

Agent loop

200K input + 10K output tokens

LongCat 2.0$0.072Fits in one request
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 LongCat 2.0 and MiniMax M2.7
SpecificationMeituan LongCat 2.0MiniMax M2.7
MakerMeituanMiniMax
WeightsOpen weightsOpen weights
ReleasedJuly 20, 2026March 18, 2026
Context window1.05M205K
Input $/Mtok$0.30$0.30
Output $/Mtok$1.20$1.20
Coding indexNot benchmarked36.2
Independent measurements behind it03
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is LongCat 2.0 better than MiniMax M2.7 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; LongCat 2.0 has none, so the two cannot be ranked on coding. Pick LongCat 2.0 for a larger context window (1.05M against 205K tokens) and work measured by ALE-Bench or Humanity's Last Exam (Artificial Analysis run), where it leads.

Which is cheaper, LongCat 2.0 or MiniMax M2.7?

LongCat 2.0 costs $0.30 per million input tokens and $1.20 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, LongCat 2.0 or MiniMax M2.7?

LongCat 2.0, with 1.05M tokens against 205K.

How many benchmarks is the LongCat 2.0 vs MiniMax M2.7 comparison based on?

8 benchmarks have a result for both models as of October 22, 2026. LongCat 2.0's coding index rests on 0 independent benchmarks and MiniMax M2.7's on 3. Where only one model has a result, the page says so instead of naming a winner.

Compare next