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GLM 4.5 Air vs Kimi K2.7 Code

Updated October 21, 2026. 14 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

GLM 4.5 AirZ.ai
Coding
No data
Overall
11.1
Output $/M
$1.10
0
Kimi K2.7 CodeMoonshot AI
Coding
53.4
Overall
25.8
Output $/M
$4.00
14
vs boards won of 14 shared

Decision reading

Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; GLM 4.5 Air has none, so the two cannot be ranked on coding.

GLM 4.5 Air has the edge where output tokens cost 3.6x less.

Shared results
14
GLM 4.5 Air only
33
Kimi K2.7 Code only
37
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
GLM 4.5 Air not benchmarked, Kimi K2.7 Code 53.4 from 4 benchmarks.
Widest category
Agentic work, 43.6 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 Air 46.5% against Kimi K2.7 Code 90.1%, 43.6 points apart on a 0 to 100 scale.
Output price
GLM 4.5 Air $1.10 against Kimi K2.7 Code $4.00 per million output tokens, 3.6x apart.
Context window
GLM 4.5 Air takes 131K 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
CategoryGLM 4.5 AirBarsKimi K2.7 CodeTies
Coding01
Intelligence01
Agentic work01
Reasoning02
Web design07
General02
All shared boards014
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi K2.7 CodeLeader
LMArena WebDevNot measured1474Only Kimi K2.7 Code measured
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)68.4%Not measuredOnly GLM 4.5 Air measured
SciCodeNot measured47.8%Only Kimi K2.7 Code measured
Terminal-Bench Hard (Artificial Analysis run)20.5%44.7%Kimi K2.7 Code
FrontierCodeNot measured30.1%Only Kimi K2.7 Code measured
GSO-Bench2.9%Not measuredOnly GLM 4.5 Air measured
WeirdMLNot measured54.1%Only Kimi K2.7 Code measured
ALE-BenchNot measured886.2Only Kimi K2.7 Code measured
LMArena Text: coding1397Not measuredOnly GLM 4.5 Air measured
LMArena Text: software and IT1401Not measuredOnly GLM 4.5 Air measured
LMArena WebDev: ReactNot measured1475Only Kimi K2.7 Code measured
LMArena WebDev: HTMLNot measured1451Only Kimi K2.7 Code measured
LMArena WebDev: from an imageNot measured1513Only Kimi K2.7 Code measured
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi K2.7 CodeLeader
AA Intelligence Index11.125.8Kimi 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 GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi 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 measured1131Only 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 Telecom46.5%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 GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi K2.7 CodeLeader
GPQA Diamond (Artificial Analysis run)73.3%89.6%Kimi K2.7 Code
Humanity's Last Exam (Artificial Analysis run)7.0%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
LMArena Text: hard prompts1379Not measuredOnly GLM 4.5 Air measured
LMArena Text: expert1370Not measuredOnly GLM 4.5 Air measured
LMArena Text: hard prompts in English1388Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi K2.7 CodeLeader
AA Math Index80.7Not measuredOnly GLM 4.5 Air measured
AIME 2025 (Artificial Analysis run)80.7%Not measuredOnly GLM 4.5 Air 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
LMArena Text: math1396Not measuredOnly GLM 4.5 Air measured
LMArena Text: mathematical work1396Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 6 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi K2.7 CodeLeader
MMLU Pro (Artificial Analysis run)81.5%Not measuredOnly GLM 4.5 Air measured
SimpleQA VerifiedNot measured36.5%Only Kimi K2.7 Code measured
LMArena Text: science1407Not measuredOnly GLM 4.5 Air measured
LMArena Text: medicine and healthcare1402Not measuredOnly GLM 4.5 Air measured
LMArena Text: legal and government1382Not measuredOnly GLM 4.5 Air measured
LMArena Text: business and finance1371Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi K2.7 CodeLeader
Design Arena: websites11471264Kimi K2.7 Code
Design Arena: UI components11231259Kimi K2.7 Code
Design Arena: game dev10941220Kimi K2.7 Code
Design Arena: data viz11861227Kimi K2.7 Code
Design Arena: 3D11221241Kimi K2.7 Code
Design Arena: all code categories11371253Kimi K2.7 Code
Design Arena: SVG10711176Kimi K2.7 Code
Design Arena: ASCII artNot measured1196Only Kimi K2.7 Code measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi K2.7 CodeLeader
IFBench37.6%63.1%Kimi K2.7 Code
Long context reasoning (AA-LCR)46.7%79.3%Kimi K2.7 Code
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
LMArena Text1384Not measuredOnly GLM 4.5 Air measured
LMArena Text: instruction following1354Not measuredOnly GLM 4.5 Air measured
LMArena Text: creative writing1343Not measuredOnly GLM 4.5 Air measured
LMArena Text: English1397Not measuredOnly GLM 4.5 Air measured
LMArena Text: non-English1366Not measuredOnly GLM 4.5 Air measured
LMArena Text: Chinese1426Not measuredOnly GLM 4.5 Air measured
LMArena Text: German1377Not measuredOnly GLM 4.5 Air measured
LMArena Text: Japanese1348Not measuredOnly GLM 4.5 Air measured
LMArena Text: Korean1308Not measuredOnly GLM 4.5 Air measured
LMArena Text: French1400Not measuredOnly GLM 4.5 Air measured
LMArena Text: Spanish1385Not measuredOnly GLM 4.5 Air measured
LMArena Text: Russian1373Not measuredOnly GLM 4.5 Air measured
LMArena Text: Polish1368Not measuredOnly GLM 4.5 Air measured
LMArena Text: multi-turn1371Not measuredOnly GLM 4.5 Air measured
LMArena Text: longer queries1366Not measuredOnly GLM 4.5 Air measured
LMArena Text: writing and language1354Not measuredOnly GLM 4.5 Air measured
LMArena Text: entertainment and media1339Not measuredOnly GLM 4.5 Air 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 GLM 4.5 Air and Kimi K2.7 Code
BenchmarkGLM 4.5 AirKimi 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

GLM 4.5 Air$0.0008Fits in one request
Kimi K2.7 Code$0.0029Fits in one request

GLM 4.5 Air costs less

Repository review

50K input + 3K output tokens

GLM 4.5 Air$0.013Fits in one request
Kimi K2.7 Code$0.059Fits in one request

GLM 4.5 Air costs less

Agent loop

200K input + 10K output tokens

GLM 4.5 Air$0.051Exceeds the context window
Kimi K2.7 Code$0.230Fits in one request

GLM 4.5 Air 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 GLM 4.5 Air and Kimi K2.7 Code
SpecificationZ.ai GLM 4.5 AirMoonshotAI Kimi K2.7 Code
MakerZ.aiMoonshot AI
WeightsOpen weightsOpen weights
ReleasedJuly 25, 2025June 12, 2026
Context window131K262K
Input $/Mtok$0.20$0.95
Output $/Mtok$1.10$4.00
Coding indexNot benchmarked53.4
Independent measurements behind it04
Cost per solved taskNot computable$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 Air better than Kimi K2.7 Code for coding?

Only Kimi K2.7 Code has a coding score, 53.4 on the Vibe Coding Index; GLM 4.5 Air has none, so the two cannot be ranked on coding. GLM 4.5 Air has the edge where output tokens cost 3.6x less.

Which is cheaper, GLM 4.5 Air or Kimi K2.7 Code?

GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Cost per solved task is known for Kimi K2.7 Code only.

Which has the bigger context window, GLM 4.5 Air or Kimi K2.7 Code?

Kimi K2.7 Code, with 262K tokens against 131K.

How many benchmarks is the GLM 4.5 Air vs Kimi K2.7 Code comparison based on?

14 benchmarks have a result for both models as of October 21, 2026. GLM 4.5 Air's coding index rests on 0 independent benchmarks and Kimi K2.7 Code's on 4. Where only one model has a result, the page says so instead of naming a winner.

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