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GPT-5.1-Codex-Mini vs Kimi K2.7 Code

Updated October 21, 2026. 17 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-5.1-Codex-Mini Replace Kimi K2.7 Code
GPT-5.1-Codex-MiniOpenAI
Coding
6.2
Overall
20.4
Output $/M
$2.00
1
Kimi K2.7 CodeMoonshot AI
Coding
39.1
Overall
25.8
Output $/M
$3.35
16
vs boards won of 17 shared

Decision reading

Pick Kimi K2.7 Code for coding: it scores 39.1 on the Vibe Coding Index against 6.2 for GPT-5.1-Codex-Mini.

Pick GPT-5.1-Codex-Mini when output tokens cost 1.7x less, or when the context window is larger, 400K against 262K tokens.

Model AGPT-5.1-Codex-MiniOpenAI6.2/1001 independent benchmarkNo cost per solved taskModel BKimi K2.7 CodeMoonshot AI39.1/1001 independent benchmark$0.35 per solved task
Shared results
17
GPT-5.1-Codex-Mini only
5
Kimi K2.7 Code only
34
Like-for-like categories
6 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
GPT-5.1-Codex-Mini 6.2 from 1 benchmark, Kimi K2.7 Code 39.1 from 1 benchmark.
Widest category
Agentic work, 27.2 points apart on average over 1 shared benchmark.
Widest single gap
LMArena WebDev: HTML: GPT-5.1-Codex-Mini 1253 against Kimi K2.7 Code 1451, 33.0 points apart on a 0 to 100 scale.
Output price
GPT-5.1-Codex-Mini $2.00 against Kimi K2.7 Code $3.35 per million output tokens, 1.7x apart.
Context window
GPT-5.1-Codex-Mini takes 400K tokens, Kimi K2.7 Code 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
CategoryGPT-5.1-Codex-MiniBarsKimi K2.7 CodeTies
Coding03
Intelligence01
Agentic work01
Reasoning02
Web design08
General11
All shared boards116
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
LMArena WebDev12441474Kimi K2.7 Code
AA Coding IndexNot measured60.8Only Kimi K2.7 Code measured
LiveCodeBench (Vals AI)Not measured82.0%Only Kimi K2.7 Code measured
SWE-bench Verified (Vals AI)Not measured78.2%Only Kimi K2.7 Code measured
Vibe Code Bench (Vals AI)Not measured47.2%Only Kimi K2.7 Code measured
Code migration (Vals AI)Not measured25.4%Only Kimi K2.7 Code measured
ProgramBench (Vals AI)Not measured0.0%Only Kimi K2.7 Code measured
Terminal-Bench 2.1 (Vals AI)Not measured67.0%Only Kimi K2.7 Code measured
SkillsBench (Vals AI)Not measured50.0%Only Kimi K2.7 Code measured
LiveCodeBench (Artificial Analysis run)83.6%Not measuredOnly GPT-5.1-Codex-Mini measured
SciCodeNot measured47.8%Only Kimi K2.7 Code measured
Terminal-Bench Hard (Artificial Analysis run)33.3%44.7%Kimi K2.7 Code
Terminal-Bench61.6%Not measuredOnly GPT-5.1-Codex-Mini measured
FrontierCodeNot measured30.1%Only Kimi K2.7 Code measured
WeirdMLNot measured54.1%Only Kimi K2.7 Code measured
ALE-BenchNot measured886.2Only Kimi K2.7 Code measured
LMArena WebDev: ReactNot measured1475Only Kimi K2.7 Code measured
LMArena WebDev: HTML12531451Kimi K2.7 Code
LMArena WebDev: from an imageNot measured1513Only Kimi K2.7 Code measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
AA Intelligence Index20.425.8Kimi K2.7 Code
Epoch Capabilities IndexNot measured150.1Only Kimi K2.7 Code measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
AA Agentic IndexNot measured21.0Only Kimi K2.7 Code measured
Design Arena: agents building web appsNot measured1176Only Kimi K2.7 Code measured
Design Arena: agents building full-stack appsNot measured1175Only Kimi K2.7 Code measured
Design Arena: agents building mobile appsNot measured1143Only Kimi K2.7 Code measured
Design Arena: agents building Android appsNot measured1143Only Kimi K2.7 Code measured
Design Arena: agents building Godot gamesNot measured1147Only Kimi K2.7 Code measured
Design Arena: agents building gamesNot measured1130Only Kimi K2.7 Code measured
Design Arena: HTML slidesNot measured1201Only Kimi K2.7 Code measured
Design Arena: PowerPoint slidesNot measured1154Only Kimi K2.7 Code measured
τ²-Bench Telecom62.9%90.1%Kimi K2.7 Code
APEX-AgentsNot measured37.6%Only Kimi K2.7 Code measured
Vending-Bench 2Not measured$5,083Only Kimi K2.7 Code measured
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
GPQA Diamond (Artificial Analysis run)81.3%89.6%Kimi K2.7 Code
Humanity's Last Exam (Artificial Analysis run)18.5%35.0%Kimi K2.7 Code
GPQA Diamond (Epoch AI run)Not measured87.9%Only Kimi K2.7 Code measured
SimpleBenchNot measured57.9%Only Kimi K2.7 Code measured
Chess puzzlesNot measured14.0%Only Kimi K2.7 Code measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
AA Math Index91.7Not measuredOnly GPT-5.1-Codex-Mini measured
AIME 2025 (Artificial Analysis run)91.7%Not measuredOnly GPT-5.1-Codex-Mini measured
OTIS Mock AIMENot measured95.6%Only Kimi K2.7 Code measured
FrontierMath, tiers 1 to 3Not measured54.0%Only Kimi K2.7 Code measured
FrontierMath, tier 4Not measured12.2%Only Kimi K2.7 Code measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Knowledge benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
MMLU Pro (Artificial Analysis run)82.0%Not measuredOnly GPT-5.1-Codex-Mini measured
SimpleQA VerifiedNot measured36.5%Only Kimi K2.7 Code measured
Neither model has a result on the other 15 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
Design Arena: websites11111264Kimi K2.7 Code
Design Arena: UI components10811259Kimi K2.7 Code
Design Arena: game dev10931220Kimi K2.7 Code
Design Arena: data viz10971226Kimi K2.7 Code
Design Arena: 3D9881241Kimi K2.7 Code
Design Arena: all code categories10941253Kimi K2.7 Code
Design Arena: SVG9771176Kimi K2.7 Code
Design Arena: ASCII art11041196Kimi K2.7 Code
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
IFBench67.9%63.1%GPT-5.1-Codex-Mini
Long context reasoning (AA-LCR)66.7%79.3%Kimi K2.7 Code
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
Neither model has a result on the other 43 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.1-Codex-Mini and Kimi K2.7 Code
BenchmarkGPT-5.1-Codex-MiniKimi K2.7 CodeLeader
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

GPT-5.1-Codex-Mini$0.0013Fits in one request
Kimi K2.7 Code$0.0023Fits in one request

GPT-5.1-Codex-Mini costs less

Repository review

50K input + 3K output tokens

GPT-5.1-Codex-Mini$0.018Fits in one request
Kimi K2.7 Code$0.044Fits in one request

GPT-5.1-Codex-Mini costs less

Agent loop

200K input + 10K output tokens

GPT-5.1-Codex-Mini$0.070Fits in one request
Kimi K2.7 Code$0.168Fits in one request

GPT-5.1-Codex-Mini 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 GPT-5.1-Codex-Mini and Kimi K2.7 Code
SpecificationOpenAI GPT-5.1-Codex-MiniMoonshotAI Kimi K2.7 Code
MakerOpenAIMoonshot AI
WeightsNo public weights listedOpen weights
ReleasedNovember 13, 2025June 12, 2026
Context window400K262K
Input $/Mtok$0.25$0.6712
Output $/Mtok$2.00$3.35
Coding index6.239.1
Independent measurements behind it11
Cost per solved taskNot computable$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.1-Codex-Mini better than Kimi K2.7 Code for coding?

Pick Kimi K2.7 Code for coding: it scores 39.1 on the Vibe Coding Index against 6.2 for GPT-5.1-Codex-Mini. Pick GPT-5.1-Codex-Mini when output tokens cost 1.7x less, or when the context window is larger, 400K against 262K tokens.

Which is cheaper, GPT-5.1-Codex-Mini or Kimi K2.7 Code?

GPT-5.1-Codex-Mini costs $0.25 per million input tokens and $2.00 per million output tokens; Kimi K2.7 Code costs $0.6712 and $3.35. Cost per solved task is known for Kimi K2.7 Code only.

Which has the bigger context window, GPT-5.1-Codex-Mini or Kimi K2.7 Code?

GPT-5.1-Codex-Mini, with 400K tokens against 262K.

How many benchmarks is the GPT-5.1-Codex-Mini vs Kimi K2.7 Code comparison based on?

17 benchmarks have a result for both models as of October 21, 2026. GPT-5.1-Codex-Mini's coding index rests on 1 independent benchmark and Kimi K2.7 Code's on 1. Where only one model has a result, the page says so instead of naming a winner.

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