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Kimi K2 0711 vs MiniMax-01

MiniMax-01 costs 2.1x less per output token than Kimi K2 0711 ($1.10 vs $2.30 per million). Updated October 21, 2026; 1 benchmarks have a result for both.

Kimi K2 0711Moonshot AI
Coding
No data
Overall
No data
Output $/M
$2.30
1
MiniMax-01MiniMax
Coding
No data
Overall
No data
Output $/M
$1.10
0
vs boards won of 1 shared

Kimi K2 0711 or MiniMax-01: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
1
Kimi K2 0711 only
36
MiniMax-01 only
0
Like-for-like categories
1 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
Kimi K2 0711 not benchmarked, MiniMax-01 not benchmarked.
Widest category
Reasoning, 21.9 points apart on average over 1 shared benchmark.
Widest single gap
Kagi LLM Benchmark: Kimi K2 0711 64.4% against MiniMax-01 42.5%, 21.9 points apart on a 0 to 100 scale.
Output price
Kimi K2 0711 $2.30 against MiniMax-01 $1.10 per million output tokens, 2.1x apart.
Context window
Kimi K2 0711 takes 131K tokens, MiniMax-01 1M.

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
CategoryKimi K2 0711BarsMiniMax-01Ties
Reasoning10
All shared boards10
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
Coding benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
Aider polyglot59.1%Not measuredOnly Kimi K2 0711 measured
SWE-bench Verified71.2%Not measuredOnly Kimi K2 0711 measured
LiveCodeBench (Vals AI)70.5%Not measuredOnly Kimi K2 0711 measured
LiveCodeBench (Artificial Analysis run)55.6%Not measuredOnly Kimi K2 0711 measured
Terminal-Bench Hard (Artificial Analysis run)15.9%Not measuredOnly Kimi K2 0711 measured
Terminal-Bench27.8%Not measuredOnly Kimi K2 0711 measured
GSO-Bench4.9%Not measuredOnly Kimi K2 0711 measured
WeirdML39.4%Not measuredOnly Kimi K2 0711 measured
Neither model has a result on the other 31 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
AA Intelligence Index12.7Not measuredOnly Kimi K2 0711 measured
Epoch Capabilities Index140.0Not measuredOnly Kimi K2 0711 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
τ²-Bench Telecom61.1%Not measuredOnly Kimi K2 0711 measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
GPQA Diamond71.5%Not measuredOnly Kimi K2 0711 measured
GPQA Diamond (Artificial Analysis run)76.6%Not measuredOnly Kimi K2 0711 measured
Humanity's Last Exam (Artificial Analysis run)7.4%Not measuredOnly Kimi K2 0711 measured
SimpleBench26.3%Not measuredOnly Kimi K2 0711 measured
Kagi LLM Benchmark64.4%42.5%Kimi K2 0711
Neither model has a result on the other 17 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
AIME62.7%Not measuredOnly Kimi K2 0711 measured
MATH 500 (Vals AI)94.2%Not measuredOnly Kimi K2 0711 measured
MGSM (Vals AI)91.0%Not measuredOnly Kimi K2 0711 measured
AA Math Index57.0Not measuredOnly Kimi K2 0711 measured
AIME 2025 (Artificial Analysis run)57.0%Not measuredOnly Kimi K2 0711 measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
MMLU Pro79.4%Not measuredOnly Kimi K2 0711 measured
LegalBench (Vals AI)81.5%Not measuredOnly Kimi K2 0711 measured
CorpFin (Vals AI)50.4%Not measuredOnly Kimi K2 0711 measured
TaxEval (Vals AI)70.2%Not measuredOnly Kimi K2 0711 measured
MedQA (Vals AI)84.0%Not measuredOnly Kimi K2 0711 measured
MMLU Pro (Artificial Analysis run)82.4%Not measuredOnly Kimi K2 0711 measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
Design Arena: websites1050Not measuredOnly Kimi K2 0711 measured
Design Arena: UI components1030Not measuredOnly Kimi K2 0711 measured
Design Arena: game dev974Not measuredOnly Kimi K2 0711 measured
Design Arena: data viz1018Not measuredOnly Kimi K2 0711 measured
Design Arena: all code categories1033Not measuredOnly Kimi K2 0711 measured
Neither model has a result on the other 4 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
General benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
IFBench41.5%Not measuredOnly Kimi K2 0711 measured
Long context reasoning (AA-LCR)53.0%Not measuredOnly Kimi K2 0711 measured
Fiction.LiveBench61.1%Not measuredOnly Kimi K2 0711 measured
Creative writing (Lech Mazur)85.6%Not measuredOnly Kimi K2 0711 measured
CL-bench11.9%Not measuredOnly Kimi K2 0711 measured
Neither model has a result on the other 41 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Kimi K2 0711 and MiniMax-01
BenchmarkKimi K2 0711MiniMax-01Leader
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

Kimi K2 0711$0.0017Fits in one request
MiniMax-01$0.0008Fits in one request

MiniMax-01 costs less

Repository review

50K input + 3K output tokens

Kimi K2 0711$0.035Fits in one request
MiniMax-01$0.013Fits in one request

MiniMax-01 costs less

Agent loop

200K input + 10K output tokens

Kimi K2 0711$0.137Exceeds the context window
MiniMax-01$0.051Fits in one request

MiniMax-01 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 Kimi K2 0711 and MiniMax-01
SpecificationMoonshotAI Kimi K2 0711MiniMax-01
MakerMoonshot AIMiniMax
WeightsOpen weightsOpen weights
ReleasedJuly 11, 2025January 15, 2025
Context window131K1M
Input $/Mtok$0.57$0.20
Output $/Mtok$2.30$1.10
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Kimi K2 0711 better than MiniMax-01 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, Kimi K2 0711 or MiniMax-01?

Kimi K2 0711 costs $0.57 per million input tokens and $2.30 per million output tokens; MiniMax-01 costs $0.20 and $1.10. Cost per solved task is known for neither of them.

Which has the bigger context window, Kimi K2 0711 or MiniMax-01?

MiniMax-01, with 1M tokens against 131K.

How many benchmarks is the Kimi K2 0711 vs MiniMax-01 comparison based on?

1 benchmarks have a result for both models as of October 21, 2026. Kimi K2 0711's coding index rests on 0 independent benchmarks and MiniMax-01's on 0. Where only one model has a result, the page says so instead of naming a winner.

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