Enter opens the highlighted result. Esc closes.

MiniMax M2.7 vs Hy3

Hy3 costs 2.3x less per output token than MiniMax M2.7 ($0.528 vs $1.20 per million). Updated October 22, 2026; 44 benchmarks have a result for both.

Replace MiniMax M2.7 Replace Hy3
MiniMax M2.7MiniMax
Coding
36.2
Overall
44.5
Output $/M
$1.20
6
Hy3Tencent
Coding
No data
Overall
No data
Output $/M
$0.528
38
vs boards won of 44 shared

MiniMax M2.7 or Hy3: which to pick

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Hy3 has none, so the two cannot be ranked on coding.

Pick Hy3 for output tokens 2.3x cheaper ($0.528 vs $1.20 per million) and a larger context window (262K against 205K tokens).

Model AMiniMax M2.7MiniMax36.2/1003 independent benchmarks$0.64 per solved taskModel BHy3TencentNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
44
MiniMax M2.7 only
30
Hy3 only
0
Like-for-like categories
6 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, Hy3 not benchmarked.
Widest category
Coding, 9.2 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena Text: Japanese: MiniMax M2.7 1260 against Hy3 1397, 22.8 points apart on a 0 to 100 scale.
Output price
MiniMax M2.7 $1.20 against Hy3 $0.528 per million output tokens, 2.3x apart.
Context window
MiniMax M2.7 takes 205K tokens, Hy3 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 M2.7BarsHy3Ties
Coding16
Reasoning05
Math02
Knowledge04
Web design53
General018
All shared boards638
CodingLike-for-likeSix of these boards feed the Vibe Coding Index16
Coding benchmarks for MiniMax M2.7 and Hy3
BenchmarkMiniMax M2.7Hy3Leader
LMArena WebDev13991507Hy3
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
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%48.6%MiniMax M2.7
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-Bench599.3838.6Hy3
LMArena Text: coding14541466Hy3
LMArena Text: software and IT14461463Hy3
LMArena WebDev: React13881511Hy3
LMArena WebDev: HTML14011487Hy3
Neither model has a result on the other 22 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for MiniMax M2.7 and Hy3
BenchmarkMiniMax M2.7Hy3Leader
AA Intelligence Index22.8Not measuredOnly MiniMax M2.7 measured
Epoch Capabilities Index145.8Not measuredOnly MiniMax M2.7 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Agentic work benchmarks for MiniMax M2.7 and Hy3
BenchmarkMiniMax M2.7Hy3Leader
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%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 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for MiniMax M2.7 and Hy3
BenchmarkMiniMax M2.7Hy3Leader
GPQA Diamond86.6%Not measuredOnly MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)87.4%89.7%Hy3
Humanity's Last Exam (Artificial Analysis run)29.6%33.5%Hy3
LMArena Text: hard prompts14221447Hy3
LMArena Text: expert14431461Hy3
LMArena Text: hard prompts in English14411455Hy3
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for MiniMax M2.7 and Hy3
BenchmarkMiniMax M2.7Hy3Leader
AIME91.0%Not measuredOnly MiniMax M2.7 measured
ProofBench3.0%Not measuredOnly MiniMax M2.7 measured
LMArena Text: math14211473Hy3
LMArena Text: mathematical work14371482Hy3
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for MiniMax M2.7 and Hy3
BenchmarkMiniMax M2.7Hy3Leader
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: science14161457Hy3
LMArena Text: medicine and healthcare14091452Hy3
LMArena Text: legal and government14031422Hy3
LMArena Text: business and finance14071424Hy3
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index53
Web design benchmarks for MiniMax M2.7 and Hy3
BenchmarkMiniMax M2.7Hy3Leader
Design Arena: websites12421230MiniMax M2.7
Design Arena: UI components12071204MiniMax M2.7
Design Arena: game dev12091208MiniMax M2.7
Design Arena: data viz12331165MiniMax M2.7
Design Arena: 3D11941232Hy3
Design Arena: all code categories12331226MiniMax M2.7
Design Arena: SVG11371200Hy3
Design Arena: ASCII art11361152Hy3
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for MiniMax M2.7 and Hy3
BenchmarkMiniMax M2.7Hy3Leader
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%79.0%Hy3
ExploitBench13.3%Not measuredOnly MiniMax M2.7 measured
LMArena Text14051438Hy3
LMArena Text: instruction following14051426Hy3
LMArena Text: creative writing13541403Hy3
LMArena Text: English14261448Hy3
LMArena Text: non-English13821426Hy3
LMArena Text: Chinese14421485Hy3
LMArena Text: German13981449Hy3
LMArena Text: Japanese12601397Hy3
LMArena Text: Korean13141396Hy3
LMArena Text: French14241456Hy3
LMArena Text: Spanish14021457Hy3
LMArena Text: Russian13831432Hy3
LMArena Text: Polish13871447Hy3
LMArena Text: multi-turn14121436Hy3
LMArena Text: longer queries14181442Hy3
LMArena Text: writing and language13761414Hy3
LMArena Text: entertainment and media13601400Hy3
Neither model has a result on the other 25 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 Hy3
BenchmarkMiniMax M2.7Hy3Leader
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
Hy3$0.0004Fits in one request

Hy3 costs less

Repository review

50K input + 3K output tokens

MiniMax M2.7$0.019Fits in one request
Hy3$0.0082Fits in one request

Hy3 costs less

Agent loop

200K input + 10K output tokens

MiniMax M2.7$0.072Exceeds the context window
Hy3$0.032Fits in one request

Hy3 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 Hy3
SpecificationMiniMax M2.7Tencent Hy3
MakerMiniMaxTencent
WeightsOpen weightsOpen weights
ReleasedMarch 18, 2026July 6, 2026
Context window205K262K
Input $/Mtok$0.30$0.132
Output $/Mtok$1.20$0.528
Coding index36.2Not benchmarked
Independent measurements behind it31
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M2.7 better than Hy3 for coding?

Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Hy3 has none, so the two cannot be ranked on coding. Pick Hy3 for output tokens 2.3x cheaper ($0.528 vs $1.20 per million) and a larger context window (262K against 205K tokens).

Which is cheaper, MiniMax M2.7 or Hy3?

MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, MiniMax M2.7 or Hy3?

Hy3, with 262K tokens against 205K.

How many benchmarks is the MiniMax M2.7 vs Hy3 comparison based on?

44 benchmarks have a result for both models as of October 22, 2026. MiniMax M2.7's coding index rests on 3 independent benchmarks and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next