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GLM 4.6 vs Kimi K2.7 Code

Kimi K2.7 Code leads GLM 4.6 on coding, 53.4 to 8.8 on the Vibe Coding Index, and GLM 4.6 costs 1.8x less per output token ($2.20 vs $4.00 per million). Updated October 22, 2026; 24 benchmarks have a result for both.

Replace GLM 4.6 Replace Kimi K2.7 Code
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
1
Kimi K2.7 CodeMoonshot AI
Coding
53.4
Overall
56.7
Output $/M
$4.00
23
vs boards won of 24 shared

GLM 4.6 or Kimi K2.7 Code: which to pick

Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for output tokens 1.8x cheaper ($2.20 vs $4.00 per million) and work measured by Design Arena: agents building Godot games, where it leads.

Model AGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved taskModel BKimi K2.7 CodeMoonshot AI53.4/1004 independent benchmarks$0.35 per solved task
Shared results
24
GLM 4.6 only
45
Kimi K2.7 Code only
27
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
GLM 4.6 8.8 from 2 benchmarks, Kimi K2.7 Code 53.4 from 4 benchmarks.
Widest category
General, 22.5 points apart on average over 2 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): GLM 4.6 3.1% against Kimi K2.7 Code 47.2%, 44.1 points apart on a 0 to 100 scale.
Output price
GLM 4.6 $2.20 against Kimi K2.7 Code $4.00 per million output tokens, 1.8x apart.
Context window
GLM 4.6 takes 205K 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 4.6BarsKimi K2.7 CodeTies
Coding07
Intelligence01
Agentic work14
Reasoning02
Web design07
General02
All shared boards123
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
Coding benchmarks for GLM 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi K2.7 CodeLeader
SWE-bench Verified68.2%Not measuredOnly GLM 4.6 measured
LMArena WebDev13411474Kimi K2.7 Code
AA Coding Index45.860.8Kimi K2.7 Code
LiveCodeBench (Vals AI)81.0%82.0%Kimi K2.7 Code
SWE-bench Verified (Vals AI)Not measured78.2%Only Kimi K2.7 Code measured
Vibe Code Bench (Vals AI)3.1%47.2%Kimi K2.7 Code
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)69.5%Not measuredOnly GLM 4.6 measured
SciCodeNot measured47.8%Only Kimi K2.7 Code measured
Terminal-Bench Hard (Artificial Analysis run)28.8%44.7%Kimi K2.7 Code
Terminal-Bench24.5%Not measuredOnly GLM 4.6 measured
FrontierCodeNot measured30.1%Only Kimi K2.7 Code measured
WeirdMLNot measured54.1%Only Kimi K2.7 Code measured
ALE-Bench340.8886.2Kimi K2.7 Code
LMArena Text: coding1449Not measuredOnly GLM 4.6 measured
LMArena Text: software and IT1455Not measuredOnly GLM 4.6 measured
LMArena WebDev: ReactNot measured1475Only Kimi K2.7 Code measured
LMArena WebDev: HTML13501451Kimi K2.7 Code
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 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi K2.7 CodeLeader
AA Intelligence Index18.525.8Kimi 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 index14
Agentic work benchmarks for GLM 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi 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 apps10291175Kimi K2.7 Code
Design Arena: agents building mobile apps10961143Kimi K2.7 Code
Design Arena: agents building Android apps10841138Kimi K2.7 Code
Design Arena: agents building Godot games11801147GLM 4.6
Design Arena: agents building gamesNot measured1130Only Kimi K2.7 Code measured
Design Arena: HTML slidesNot measured1151Only Kimi K2.7 Code measured
Design Arena: PowerPoint slidesNot measured1129Only Kimi K2.7 Code measured
τ²-Bench Telecom76.9%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
Berkeley Function Calling Leaderboard (BFCL)72.4%Not measuredOnly GLM 4.6 measured
BrowseComp-Plus48.2%Not measuredOnly GLM 4.6 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 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi K2.7 CodeLeader
GPQA Diamond74.5%Not measuredOnly GLM 4.6 measured
GPQA Diamond (Artificial Analysis run)78.0%89.6%Kimi K2.7 Code
Humanity's Last Exam (Artificial Analysis run)14.5%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
LMArena Text: hard prompts1440Not measuredOnly GLM 4.6 measured
LMArena Text: expert1432Not measuredOnly GLM 4.6 measured
LMArena Text: hard prompts in English1445Not measuredOnly GLM 4.6 measured
Kagi LLM Benchmark45.7%Not measuredOnly GLM 4.6 measured
Neither model has a result on the other 12 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Math benchmarks for GLM 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi K2.7 CodeLeader
AIME92.7%Not measuredOnly GLM 4.6 measured
MGSM (Vals AI)89.8%Not measuredOnly GLM 4.6 measured
AA Math Index86.0Not measuredOnly GLM 4.6 measured
AIME 2025 (Artificial Analysis run)86.0%Not measuredOnly GLM 4.6 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: math1432Not measuredOnly GLM 4.6 measured
LMArena Text: mathematical work1447Not measuredOnly GLM 4.6 measured
Neither model has a result on the other 4 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Knowledge benchmarks for GLM 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi K2.7 CodeLeader
MMLU Pro82.2%Not measuredOnly GLM 4.6 measured
LegalBench (Vals AI)79.6%Not measuredOnly GLM 4.6 measured
CorpFin (Vals AI)56.8%Not measuredOnly GLM 4.6 measured
TaxEval (Vals AI)66.2%Not measuredOnly GLM 4.6 measured
MedQA (Vals AI)92.2%Not measuredOnly GLM 4.6 measured
MMLU Pro (Artificial Analysis run)82.9%Not measuredOnly GLM 4.6 measured
SimpleQA VerifiedNot measured36.5%Only Kimi K2.7 Code measured
LMArena Text: science1456Not measuredOnly GLM 4.6 measured
LMArena Text: medicine and healthcare1455Not measuredOnly GLM 4.6 measured
LMArena Text: legal and government1448Not measuredOnly GLM 4.6 measured
LMArena Text: business and finance1416Not measuredOnly GLM 4.6 measured
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for GLM 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi K2.7 CodeLeader
Design Arena: websites11741263Kimi K2.7 Code
Design Arena: UI components11451255Kimi K2.7 Code
Design Arena: game dev11501220Kimi K2.7 Code
Design Arena: data viz11611227Kimi K2.7 Code
Design Arena: 3D11281240Kimi K2.7 Code
Design Arena: all code categories11651252Kimi K2.7 Code
Design Arena: SVG11081176Kimi 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 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi K2.7 CodeLeader
IFBench43.4%63.1%Kimi K2.7 Code
Long context reasoning (AA-LCR)54.0%79.3%Kimi K2.7 Code
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
LMArena Text1440Not measuredOnly GLM 4.6 measured
LMArena Text: instruction following1410Not measuredOnly GLM 4.6 measured
LMArena Text: creative writing1412Not measuredOnly GLM 4.6 measured
LMArena Text: English1449Not measuredOnly GLM 4.6 measured
LMArena Text: non-English1426Not measuredOnly GLM 4.6 measured
LMArena Text: Chinese1499Not measuredOnly GLM 4.6 measured
LMArena Text: German1447Not measuredOnly GLM 4.6 measured
LMArena Text: Japanese1393Not measuredOnly GLM 4.6 measured
LMArena Text: Korean1400Not measuredOnly GLM 4.6 measured
LMArena Text: French1459Not measuredOnly GLM 4.6 measured
LMArena Text: Spanish1436Not measuredOnly GLM 4.6 measured
LMArena Text: Russian1418Not measuredOnly GLM 4.6 measured
LMArena Text: Polish1447Not measuredOnly GLM 4.6 measured
LMArena Text: multi-turn1427Not measuredOnly GLM 4.6 measured
LMArena Text: longer queries1422Not measuredOnly GLM 4.6 measured
LMArena Text: writing and language1415Not measuredOnly GLM 4.6 measured
LMArena Text: entertainment and media1409Not measuredOnly GLM 4.6 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 4.6 and Kimi K2.7 Code
BenchmarkGLM 4.6Kimi 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 4.6$0.0017Fits in one request
Kimi K2.7 Code$0.0029Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

GLM 4.6$0.037Fits in one request
Kimi K2.7 Code$0.059Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

GLM 4.6$0.142Exceeds the context window
Kimi K2.7 Code$0.230Fits in one request

GLM 4.6 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 4.6 and Kimi K2.7 Code
SpecificationZ.ai GLM 4.6MoonshotAI Kimi K2.7 Code
MakerZ.aiMoonshot AI
WeightsOpen weightsOpen weights
ReleasedSeptember 30, 2025June 12, 2026
Context window205K262K
Input $/Mtok$0.60$0.95
Output $/Mtok$2.20$4.00
Coding index8.853.4
Independent measurements behind it24
Cost per solved taskNot computable$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.6 better than Kimi K2.7 Code for coding?

Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for output tokens 1.8x cheaper ($2.20 vs $4.00 per million) and work measured by Design Arena: agents building Godot games, where it leads.

Which is cheaper, GLM 4.6 or Kimi K2.7 Code?

GLM 4.6 costs $0.60 per million input tokens and $2.20 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 4.6 or Kimi K2.7 Code?

Kimi K2.7 Code, with 262K tokens against 205K.

How many benchmarks is the GLM 4.6 vs Kimi K2.7 Code comparison based on?

24 benchmarks have a result for both models as of October 22, 2026. GLM 4.6's coding index rests on 2 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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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/glm-4-6-vs-kimi-k2-7-code">LLMBenchmark.ai, GLM 4.6 vs Kimi K2.7 Code</a></p>