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MiniMax M2.7 vs Hy4

Hy4 leads MiniMax M2.7 on coding, 65.2 to 36.2 on the Vibe Coding Index, at about the same output price ($1.2505 vs $1.20 per million). Updated November 5, 2026; 3 benchmarks have a result for both.

MiniMax M2.7MiniMax
Coding
36.2
Overall
No data
Output $/M
$1.20
0
Hy4Tencent
Coding
65.2
Overall
No data
Output $/M
$1.2505
3
vs boards won of 3 shared

MiniMax M2.7 or Hy4: which to pick

Pick Hy4 for coding: it scores 65.2 on the Vibe Coding Index against 36.2 for MiniMax M2.7, though on 2 benchmarks against 3.

Pick MiniMax M2.7 for output tokens 1.0x cheaper ($1.20 vs $1.2505 per million).

Shared results
3
MiniMax M2.7 only
71
Hy4 only
3
Like-for-like categories
2 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, Hy4 65.2 from 2 benchmarks.
Widest category
Coding, 69.1 points apart on average over 1 shared benchmark.
Widest single gap
Vibe Code Bench (Vals AI): MiniMax M2.7 11.9% against Hy4 81.0%, 69.1 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Hy4 $1.2505 per million output tokens, 1.0x apart.
Context window
MiniMax M2.7 takes 205K tokens, Hy4 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 M2.7BarsHy4Ties
Coding01
Agentic work02
All shared boards03
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for MiniMax M2.7 and Hy4
BenchmarkMiniMax M2.7Hy4Leader
LMArena WebDev1398Not 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
Terminal-Bench 4 (Vals AI)Not measured39.4%Only Hy4 measured
Vibe Code Bench (Vals AI)11.9%81.0%Hy4
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: coding1454Not measuredOnly MiniMax M2.7 measured
LMArena Text: software and IT1445Not measuredOnly MiniMax M2.7 measured
LMArena WebDev: React1388Not measuredOnly MiniMax M2.7 measured
LMArena WebDev: HTML1401Not measuredOnly MiniMax M2.7 measured
Terminal-Bench 2.045.1%Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 31 boards here
IntelligenceNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Intelligence benchmarks for MiniMax M2.7 and Hy4
BenchmarkMiniMax M2.7Hy4Leader
Neither model has a result on 2 boards here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for MiniMax M2.7 and Hy4
BenchmarkMiniMax M2.7Hy4Leader
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%34.4%Hy4
Legal Research Bench (Vals AI)10.6%41.4%Hy4
Harvey's Legal Agent Benchmark (Vals AI)Not measured12.5%Only Hy4 measured
Excel Modeling Benchmark (Vals AI)28.4%Not measuredOnly MiniMax M2.7 measured
τ²-Bench Telecom84.8%Not measuredOnly MiniMax M2.7 measured
Toolathlon-Verified47.5%Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 36 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Reasoning benchmarks for MiniMax M2.7 and Hy4
BenchmarkMiniMax M2.7Hy4Leader
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 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 18 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for MiniMax M2.7 and Hy4
BenchmarkMiniMax M2.7Hy4Leader
AIME91.0%Not measuredOnly MiniMax M2.7 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 10 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Knowledge benchmarks for MiniMax M2.7 and Hy4
BenchmarkMiniMax M2.7Hy4Leader
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: science1416Not measuredOnly MiniMax M2.7 measured
LMArena Text: medicine and healthcare1410Not 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 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 Hy4
BenchmarkMiniMax M2.7Hy4Leader
Design Arena: websites1241Not measuredOnly MiniMax M2.7 measured
Design Arena: UI components1206Not measuredOnly MiniMax M2.7 measured
Design Arena: game dev1208Not measuredOnly MiniMax M2.7 measured
Design Arena: data viz1233Not measuredOnly MiniMax M2.7 measured
Design Arena: 3D1191Not measuredOnly MiniMax M2.7 measured
Design Arena: all code categories1232Not measuredOnly MiniMax M2.7 measured
Design Arena: SVG1132Not measuredOnly MiniMax M2.7 measured
Design Arena: ASCII art1133Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index22 boards, none shared
General benchmarks for MiniMax M2.7 and Hy4
BenchmarkMiniMax M2.7Hy4Leader
Vals IndexNot measured59.4%Only Hy4 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
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-English1383Not measuredOnly MiniMax M2.7 measured
LMArena Text: Chinese1441Not measuredOnly MiniMax M2.7 measured
LMArena Text: German1398Not measuredOnly MiniMax M2.7 measured
LMArena Text: Japanese1256Not measuredOnly MiniMax M2.7 measured
LMArena Text: Korean1313Not measuredOnly MiniMax M2.7 measured
LMArena Text: French1425Not measuredOnly MiniMax M2.7 measured
LMArena Text: Spanish1404Not measuredOnly MiniMax M2.7 measured
LMArena Text: Russian1383Not measuredOnly MiniMax M2.7 measured
LMArena Text: Polish1388Not measuredOnly MiniMax M2.7 measured
LMArena Text: multi-turn1412Not measuredOnly MiniMax M2.7 measured
LMArena Text: longer queries1419Not measuredOnly MiniMax M2.7 measured
LMArena Text: writing and language1377Not measuredOnly MiniMax M2.7 measured
LMArena Text: entertainment and media1360Not measuredOnly MiniMax M2.7 measured
Neither model has a result on the other 26 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 Hy4
BenchmarkMiniMax M2.7Hy4Leader
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
Hy4$0.0010Fits in one request

MiniMax M2.7 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Hy4$0.025Fits in one request

MiniMax M2.7 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Hy4$0.096Fits 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 Hy4
SpecificationMiniMax M2.7Tencent Hy4
MakerMiniMaxTencent
WeightsOpen weightsOpen weights
ReleasedMarch 18, 2026November 4, 2026
Context window205K1.05M
Input $/Mtok$0.30$0.417
Output $/Mtok$1.20$1.2505
Coding index36.265.2
Independent measurements behind it32
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than Hy4 for coding?

Pick Hy4 for coding: it scores 65.2 on the Vibe Coding Index against 36.2 for MiniMax M2.7, though on 2 benchmarks against 3. Pick MiniMax M2.7 for output tokens 1.0x cheaper ($1.20 vs $1.2505 per million).

Which is cheaper, MiniMax M2.7 or Hy4?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Hy4 costs $0.417 and $1.2505. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Hy4?

Hy4, with 1.05M tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs Hy4 comparison based on?

3 benchmarks have a result for both models as of November 5, 2026. MiniMax M2.7's coding index rests on 3 independent benchmarks and Hy4's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/minimax-minimax-m2-7-vs-tencent-hy4">LLMBenchmark.ai, MiniMax M2.7 vs Hy4</a></p>