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GLM 4.7 vs Kimi K3

Kimi K3 leads GLM 4.7 on coding, 62.3 to 55.1 on the Vibe Coding Index, and GLM 4.7 costs 6.8x less per output token ($2.20 vs $15.00 per million). Updated October 22, 2026; 66 benchmarks have a result for both.

Replace GLM 4.7 Replace Kimi K3
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
0
Kimi K3Moonshot AI
Coding
62.3
Overall
66.5
Output $/M
$15.00
66
vs boards won of 66 shared

GLM 4.7 or Kimi K3: which to pick

Pick Kimi K3 for coding: it scores 62.3 on the Vibe Coding Index against 55.1 for GLM 4.7.

Pick GLM 4.7 for output tokens 6.8x cheaper ($2.20 vs $15.00 per million) and a lower cost per solved task ($0.29 against $0.81).

Model AGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved taskModel BKimi K3Moonshot AI62.3/1006 independent benchmarks$0.81 per solved task
Shared results
66
GLM 4.7 only
16
Kimi K3 only
56
Like-for-like categories
8 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 4.7 55.1 from 2 benchmarks, Kimi K3 62.3 from 6 benchmarks.
Widest category
Math, 30.5 points apart on average over 4 shared benchmarks.
Widest single gap
ProofBench: GLM 4.7 6.0% against Kimi K3 87.0%, 81.0 points apart on a 0 to 100 scale.
Output price
GLM 4.7 $2.20 against Kimi K3 $15.00 per million output tokens, 6.8x apart.
Context window
GLM 4.7 takes 205K tokens, Kimi K3 1.05M.

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 4.7BarsKimi K3Ties
Coding09
Intelligence02
Agentic work06
Reasoning09
Math04
Knowledge010
Web design07
General019
All shared boards066
CodingLike-for-likeSix of these boards feed the Vibe Coding Index09
Coding benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
LiveBench codingNot measured59.3%Only Kimi K3 measured
LMArena WebDev14351655Kimi K3
AA Coding Index45.376.2Kimi K3
LiveCodeBench (Vals AI)82.2%87.2%Kimi K3
SWE-bench Verified (Vals AI)69.4%93.4%Kimi K3
Terminal-Bench 4 (Vals AI)Not measured17.2%Only Kimi K3 measured
Vibe Code Bench (Vals AI)Not measured85.0%Only Kimi K3 measured
Code migration (Vals AI)Not measured16.1%Only Kimi K3 measured
ProgramBench (Vals AI)Not measured2.0%Only Kimi K3 measured
IOI (Vals AI)Not measured48.9%Only Kimi K3 measured
Terminal-Bench 2.1 (Vals AI)Not measured80.9%Only Kimi K3 measured
SWE-bench Multimodal (Vals AI)Not measured44.2%Only Kimi K3 measured
Vibe Code Bench 1-100 (Vals AI)Not measured18.2%Only Kimi K3 measured
CyberBench (Vals AI)Not measured75.2%Only Kimi K3 measured
LiveCodeBench (Artificial Analysis run)89.4%Not measuredOnly GLM 4.7 measured
SciCodeNot measured59.5%Only Kimi K3 measured
Terminal-Bench Hard (Artificial Analysis run)31.8%Not measuredOnly GLM 4.7 measured
Terminal-Bench33.4%Not measuredOnly GLM 4.7 measured
FrontierCodeNot measured44.2%Only Kimi K3 measured
FrontierSWENot measured25.9%Only Kimi K3 measured
WeirdMLNot measured82.6%Only Kimi K3 measured
ALE-Bench399.51524.5Kimi K3
LMArena Text: coding14541508Kimi K3
LMArena Text: software and IT14531499Kimi K3
LMArena WebDev: React14201670Kimi K3
LMArena WebDev: HTML14471644Kimi K3
LMArena WebDev: from an imageNot measured1579Only Kimi K3 measured
SWE-Bench Pro V2Not measured97.7%Only Kimi K3 measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
AA Intelligence Index22.243.6Kimi K3
Epoch Capabilities Index143.6157.9Kimi K3
Agentic workLike-for-likePublic boards, shown as published, kept out of the index06
Agentic work benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
AA Agentic IndexNot measured50.0Only Kimi K3 measured
Design Arena: agents building web appsNot measured1295Only Kimi K3 measured
Design Arena: agents building full-stack apps10501315Kimi K3
Design Arena: agents building mobile apps11051268Kimi K3
Design Arena: agents building Android apps11121252Kimi K3
Design Arena: agents building Godot games10581223Kimi K3
Design Arena: agents building gamesNot measured1252Only Kimi K3 measured
Design Arena: HTML slidesNot measured1196Only Kimi K3 measured
Design Arena: PowerPoint slidesNot measured1245Only Kimi K3 measured
Design Arena: spreadsheetsNot measured1096Only Kimi K3 measured
LiveBench researchNot measured79.0%Only Kimi K3 measured
LiveBench browserNot measured16.0%Only Kimi K3 measured
LiveBench long agenticNot measured42.8%Only Kimi K3 measured
Finance Agent (Vals AI)Not measured53.1%Only Kimi K3 measured
Tax Agent Bench (Vals AI)Not measured33.4%Only Kimi K3 measured
Legal Research Bench (Vals AI)Not measured46.1%Only Kimi K3 measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured12.9%Only Kimi K3 measured
Excel Modeling Benchmark (Vals AI)Not measured66.7%Only Kimi K3 measured
BioMysteryBench (Vals AI)Not measured72.6%Only Kimi K3 measured
Terminal-Bench-Science (Vals AI)Not measured1.4%Only Kimi K3 measured
Time Horizon Index (Vals AI)Not measured10.5%Only Kimi K3 measured
τ²-Bench Telecom95.9%Not measuredOnly GLM 4.7 measured
APEX-AgentsNot measured47.8%Only Kimi K3 measured
PostTrainBenchNot measured32.0%Only Kimi K3 measured
Vending-Bench 2$2,377$5,165Kimi K3
BrowseComp-Plus64.7%Not measuredOnly GLM 4.7 measured
MCP Atlas58.1%82.3%Kimi K3
Neither model has a result on the other 15 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
GPQA Diamond80.0%92.9%Kimi K3
LiveBench reasoningNot measured90.7%Only Kimi K3 measured
MMMU Pro (Vals AI)Not measured88.2%Only Kimi K3 measured
GPQA Diamond (Artificial Analysis run)85.9%93.5%Kimi K3
Humanity's Last Exam (Artificial Analysis run)27.4%46.9%Kimi K3
GPQA Diamond (Epoch AI run)83.3%93.1%Kimi K3
ARC-AGINot measured94.5%Only Kimi K3 measured
ARC-AGI-2Not measured60.4%Only Kimi K3 measured
SimpleBench47.7%60.7%Kimi K3
Chess puzzles21.0%37.0%Kimi K3
Mystery game puzzlesNot measured26.0%Only Kimi K3 measured
LMArena Text: hard prompts14431495Kimi K3
LMArena Text: expert14241520Kimi K3
LMArena Text: hard prompts in English14521496Kimi K3
Humanity's Last Exam (Scale run)Not measured22.2%Only Kimi K3 measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
AIME93.3%Not measuredOnly GLM 4.7 measured
MGSM (Vals AI)88.2%Not measuredOnly GLM 4.7 measured
AA Math Index95.0Not measuredOnly GLM 4.7 measured
AIME 2025 (Artificial Analysis run)95.0%Not measuredOnly GLM 4.7 measured
OTIS Mock AIME83.3%97.2%Kimi K3
FrontierMath, tiers 1 to 3Not measured72.2%Only Kimi K3 measured
FrontierMath, tier 4Not measured39.0%Only Kimi K3 measured
ProofBench6.0%87.0%Kimi K3
LMArena Text: math14241494Kimi K3
LMArena Text: mathematical work14111505Kimi K3
MathArenaNot measured48.0%Only Kimi K3 measured
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
Knowledge benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
MMLU Pro82.7%88.0%Kimi K3
LegalBench (Vals AI)83.4%86.2%Kimi K3
CaseLaw (Vals AI)54.9%Not measuredOnly GLM 4.7 measured
CorpFin (Vals AI)46.4%71.6%Kimi K3
TaxEval (Vals AI)68.8%75.7%Kimi K3
MortgageTax (Vals AI)Not measured66.3%Only Kimi K3 measured
MedQA (Vals AI)93.7%Not measuredOnly GLM 4.7 measured
MedCode (Vals AI)32.8%49.4%Kimi K3
MMLU Pro (Artificial Analysis run)85.6%Not measuredOnly GLM 4.7 measured
SimpleQA Verified32.2%50.6%Kimi K3
LMArena Text: science14571508Kimi K3
LMArena Text: medicine and healthcare14691489Kimi K3
LMArena Text: legal and government14441503Kimi K3
LMArena Text: business and finance14291470Kimi K3
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
Design Arena: websites12251335Kimi K3
Design Arena: UI components11971340Kimi K3
Design Arena: game dev11881360Kimi K3
Design Arena: data viz11961352Kimi K3
Design Arena: 3D11901387Kimi K3
Design Arena: all code categories12161360Kimi K3
Design Arena: SVG11421301Kimi K3
Design Arena: ASCII art1165Not measuredOnly GLM 4.7 measured
LiveBench designNot measured77.2%Only Kimi K3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
Vals IndexNot measured53.0%Only Kimi K3 measured
LiveBench data analysisNot measured78.7%Only Kimi K3 measured
Public Benefits Bench (Vals AI)Not measured68.2%Only Kimi K3 measured
SAGE (Vals AI)Not measured52.8%Only Kimi K3 measured
MedScribe (Vals AI)68.6%88.0%Kimi K3
Vals Multimodal IndexNot measured73.4%Only Kimi K3 measured
IFBench67.9%Not measuredOnly GLM 4.7 measured
Long context reasoning (AA-LCR)71.0%88.7%Kimi K3
DTBenchNot measured91.2%Only Kimi K3 measured
LMCANot measured52.7%Only Kimi K3 measured
CL-bench15.9%Not measuredOnly GLM 4.7 measured
Surface Evolver BenchNot measured95.0%Only Kimi K3 measured
Furniture assemblyNot measured34.2%Only Kimi K3 measured
CL-bench Life10.9%Not measuredOnly GLM 4.7 measured
LMArena Text14351476Kimi K3
LMArena Text: instruction following14121485Kimi K3
LMArena Text: creative writing14011457Kimi K3
LMArena Text: English14531481Kimi K3
LMArena Text: non-English14171466Kimi K3
LMArena Text: Chinese14951529Kimi K3
LMArena Text: German14261490Kimi K3
LMArena Text: Japanese14391494Kimi K3
LMArena Text: Korean13991460Kimi K3
LMArena Text: French14321492Kimi K3
LMArena Text: Spanish14341472Kimi K3
LMArena Text: Russian14231485Kimi K3
LMArena Text: Polish14351458Kimi K3
LMArena Text: multi-turn14461489Kimi K3
LMArena Text: longer queries14321494Kimi K3
LMArena Text: writing and language14111471Kimi K3
LMArena Text: entertainment and media14001453Kimi K3
EQ-Bench 4Not measured1339Only Kimi K3 measured
Neither model has a result on the other 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.7 and Kimi K3
BenchmarkGLM 4.7Kimi K3Leader
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 4.7$0.0017Fits in one request
Kimi K3$0.011Fits in one request

GLM 4.7 costs less

Repository review

50K input + 3K output tokens

GLM 4.7$0.037Fits in one request
Kimi K3$0.195Fits in one request

GLM 4.7 costs less

Agent loop

200K input + 10K output tokens

GLM 4.7$0.142Exceeds the context window
Kimi K3$0.750Fits in one request

GLM 4.7 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 4.7 and Kimi K3
SpecificationZ.ai GLM 4.7MoonshotAI Kimi K3
MakerZ.aiMoonshot AI
WeightsOpen weightsOpen weights
ReleasedDecember 22, 2025July 16, 2026
Context window205K1.05M
Input $/Mtok$0.60$3.00
Output $/Mtok$2.20$15.00
Coding index55.162.3
Independent measurements behind it26
Cost per solved task$0.29$0.81
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 better than Kimi K3 for coding?

Pick Kimi K3 for coding: it scores 62.3 on the Vibe Coding Index against 55.1 for GLM 4.7. Pick GLM 4.7 for output tokens 6.8x cheaper ($2.20 vs $15.00 per million) and a lower cost per solved task ($0.29 against $0.81).

Which is cheaper, GLM 4.7 or Kimi K3?

GLM 4.7 costs $0.60 per million input tokens and $2.20 per million output tokens; Kimi K3 costs $3.00 and $15.00. Per solved SWE-bench Verified task, GLM 4.7 costs $0.29 and Kimi K3 $0.81.

Which has the bigger context window, GLM 4.7 or Kimi K3?

Kimi K3, with 1.05M tokens against 205K.

How many benchmarks is the GLM 4.7 vs Kimi K3 comparison based on?

66 benchmarks have a result for both models as of October 22, 2026. GLM 4.7's coding index rests on 2 independent benchmarks and Kimi K3's on 6. 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-4-7-vs-kimi-k3">LLMBenchmark.ai, GLM 4.7 vs Kimi K3</a></p>