LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

GLM 5.2 vs Kimi K2.6

Updated October 21, 2026. 88 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 5.2 Replace Kimi K2.6
GLM 5.2Z.ai
Coding
57.7
Overall
33.7
Output $/M
$7.00
71
Kimi K2.6Moonshot AI
Coding
44.2
Overall
27.0
Output $/M
$3.41
17
vs boards won of 88 shared

Decision reading

Pick GLM 5.2 for coding: it scores 57.7 on the Vibe Coding Index against 44.2 for Kimi K2.6.

Pick Kimi K2.6 when output tokens cost 2.1x less, or when a solved task costs $0.35 against $0.86.

Model AGLM 5.2Z.ai57.7/1001 independent benchmark$0.86 per solved taskModel BKimi K2.6Moonshot AI44.2/1001 independent benchmark$0.35 per solved task
Shared results
88
GLM 5.2 only
9
Kimi K2.6 only
21
Like-for-like categories
8 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 5.2 57.7 from 1 benchmark, Kimi K2.6 44.2 from 1 benchmark.
Widest category
Coding, 9.3 points apart on average over 16 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): GLM 5.2 64.0% against Kimi K2.6 37.9%, 26.1 points apart on a 0 to 100 scale.
Output price
GLM 5.2 $7.00 against Kimi K2.6 $3.41 per million output tokens, 2.1x apart.
Context window
GLM 5.2 takes 1.05M tokens, Kimi K2.6 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 5.2BarsKimi K2.6Ties
Coding124
Intelligence20
Agentic work122
Reasoning73
Math51
Knowledge55
Web design80
General202
All shared boards7117
CodingLike-for-likeFour of these boards feed the Vibe Coding Index124
Coding benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
LMArena WebDev16041509GLM 5.2
AA Coding Index68.861.8GLM 5.2
LiveCodeBench (Vals AI)69.5%86.8%Kimi K2.6
SWE-bench Verified (Vals AI)82.8%76.2%GLM 5.2
Vibe Code Bench (Vals AI)64.0%37.9%GLM 5.2
Code migration (Vals AI)37.9%27.8%GLM 5.2
ProgramBench (Vals AI)0.5%0.0%GLM 5.2
Terminal-Bench 2.1 (Vals AI)67.8%53.6%GLM 5.2
SkillsBench (Vals AI)45.1%Not measuredOnly GLM 5.2 measured
SciCode51.2%51.5%Kimi K2.6
Terminal-Bench Hard (Artificial Analysis run)50.8%43.9%GLM 5.2
FrontierCode24.5%Not measuredOnly GLM 5.2 measured
WeirdML70.1%55.9%GLM 5.2
ALE-Bench1047.01092.7Kimi K2.6
LMArena Text: coding14871489Kimi K2.6
LMArena Text: software and IT14861484GLM 5.2
LMArena WebDev: React16171505GLM 5.2
LMArena WebDev: HTML15651485GLM 5.2
LMArena WebDev: from an imageNot measured1521Only Kimi K2.6 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
AA Intelligence Index33.727.0GLM 5.2
Epoch Capabilities Index151.9150.9GLM 5.2
Agentic workLike-for-likePublic boards, shown as published, kept out of the index122
Agentic work benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
AA Agentic Index38.420.5GLM 5.2
Design Arena: agents building web apps12221268Kimi K2.6
Design Arena: agents building full-stack apps12411155GLM 5.2
Design Arena: agents building mobile apps11601156GLM 5.2
Design Arena: agents building Android apps11841166GLM 5.2
Design Arena: agents building Godot games11421120GLM 5.2
Design Arena: agents building games12061141GLM 5.2
Design Arena: HTML slides11751184Kimi K2.6
Design Arena: PowerPoint slides11951128GLM 5.2
Design Arena: spreadsheetsNot measured1276Only Kimi K2.6 measured
SREBench (Vals AI)0.0%Not measuredOnly GLM 5.2 measured
Finance Agent (Vals AI)49.7%44.9%GLM 5.2
Tax Agent Bench (Vals AI)Not measured12.4%Only Kimi K2.6 measured
Legal Research Bench (Vals AI)31.3%15.9%GLM 5.2
Excel Modeling Benchmark (Vals AI)61.5%57.9%GLM 5.2
τ²-Bench Telecom99.1%95.9%GLM 5.2
APEX-Agents45.2%Not measuredOnly GLM 5.2 measured
OSWorld 2.0Not measured4.6%Only Kimi K2.6 measured
PostTrainBench31.7%Not measuredOnly GLM 5.2 measured
Vending-Bench 2$8,314$6,205GLM 5.2
Neither model has a result on the other 19 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index73
Reasoning benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
GPQA Diamond85.6%89.1%Kimi K2.6
MMMU Pro (Vals AI)Not measured86.3%Only Kimi K2.6 measured
GPQA Diamond (Artificial Analysis run)89.5%91.1%Kimi K2.6
Humanity's Last Exam (Artificial Analysis run)41.1%37.5%GLM 5.2
GPQA Diamond (Epoch AI run)91.9%90.8%GLM 5.2
ARC-AGI77.0%Not measuredOnly GLM 5.2 measured
ARC-AGI-222.8%Not measuredOnly GLM 5.2 measured
SimpleBench58.8%Not measuredOnly GLM 5.2 measured
Chess puzzles22.0%20.0%GLM 5.2
Mystery game puzzles19.0%18.0%GLM 5.2
EBR-bench9.5%2.4%GLM 5.2
LMArena Text: hard prompts14811470GLM 5.2
LMArena Text: expert14871491Kimi K2.6
LMArena Text: hard prompts in English14811471GLM 5.2
LMArena Vision: diagramsNot measured1298Only Kimi K2.6 measured
LMArena Vision: homeworkNot measured1310Only Kimi K2.6 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index51
Math benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
OTIS Mock AIME86.4%96.1%Kimi K2.6
FrontierMath, tiers 1 to 359.2%57.2%GLM 5.2
FrontierMath, tier 429.3%25.6%GLM 5.2
ProofBench35.0%16.0%GLM 5.2
LMArena Text: math14831474GLM 5.2
LMArena Text: mathematical work14891480GLM 5.2
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index55
Knowledge benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
MMLU Pro86.7%87.6%Kimi K2.6
LegalBench (Vals AI)84.1%84.7%Kimi K2.6
CaseLaw (Vals AI)Not measured61.2%Only Kimi K2.6 measured
CorpFin (Vals AI)66.1%66.7%Kimi K2.6
TaxEval (Vals AI)73.3%74.7%Kimi K2.6
MortgageTax (Vals AI)Not measured65.8%Only Kimi K2.6 measured
MedCode (Vals AI)40.8%40.1%GLM 5.2
SimpleQA Verified34.2%34.9%Kimi K2.6
LMArena Text: science14891468GLM 5.2
LMArena Text: medicine and healthcare14751457GLM 5.2
LMArena Text: legal and government14861462GLM 5.2
LMArena Text: business and finance14511445GLM 5.2
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
Design Arena: websites12851269GLM 5.2
Design Arena: UI components12961266GLM 5.2
Design Arena: game dev12681251GLM 5.2
Design Arena: data viz12851249GLM 5.2
Design Arena: 3D12881268GLM 5.2
Design Arena: all code categories12881272GLM 5.2
Design Arena: SVG12141181GLM 5.2
Design Arena: ASCII art11901164GLM 5.2
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index202
General benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
Public Benefits Bench (Vals AI)Not measured56.6%Only Kimi K2.6 measured
SAGE (Vals AI)Not measured50.2%Only Kimi K2.6 measured
MedScribe (Vals AI)83.5%78.2%GLM 5.2
Vals Multimodal IndexNot measured56.4%Only Kimi K2.6 measured
IFBench73.3%76.0%Kimi K2.6
Long context reasoning (AA-LCR)78.3%81.0%Kimi K2.6
DTBench93.6%90.9%GLM 5.2
LMCA45.8%37.3%GLM 5.2
Surface Evolver Bench55.6%Not measuredOnly GLM 5.2 measured
Furniture assemblyNot measured21.7%Only Kimi K2.6 measured
ExploitBenchNot measured18.4%Only Kimi K2.6 measured
LMArena Text14701455GLM 5.2
LMArena Text: instruction following14661451GLM 5.2
LMArena Text: creative writing14631434GLM 5.2
LMArena VisionNot measured1282Only Kimi K2.6 measured
LMArena Text: English14751460GLM 5.2
LMArena Text: non-English14591446GLM 5.2
LMArena Text: Chinese15221520GLM 5.2
LMArena Text: German14701451GLM 5.2
LMArena Text: Japanese14501443GLM 5.2
LMArena Text: Korean14401427GLM 5.2
LMArena Text: French14791471GLM 5.2
LMArena Text: Spanish14781464GLM 5.2
LMArena Text: Russian14681446GLM 5.2
LMArena Text: Polish14561438GLM 5.2
LMArena Text: multi-turn14691453GLM 5.2
LMArena Text: longer queries14801468GLM 5.2
LMArena Text: writing and language14631439GLM 5.2
LMArena Text: entertainment and media14501428GLM 5.2
LMArena Vision: EnglishNot measured1287Only Kimi K2.6 measured
LMArena Vision: ChineseNot measured1346Only Kimi K2.6 measured
LMArena Vision: reading textNot measured1291Only Kimi K2.6 measured
LMArena Vision: humorNot measured1280Only Kimi K2.6 measured
LMArena Vision: creative writingNot measured1273Only Kimi K2.6 measured
LMArena DocumentNot measured1451Only Kimi K2.6 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.2 and Kimi K2.6
BenchmarkGLM 5.2Kimi K2.6Leader
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 5.2$0.0035Fits in one request
Kimi K2.6$0.0024Fits in one request

Kimi K2.6 costs less

Repository review

50K input + 3K output tokens

GLM 5.2$0.023Fits in one request
Kimi K2.6$0.043Fits in one request

GLM 5.2 costs less

Agent loop

200K input + 10K output tokens

GLM 5.2$0.077Fits in one request
Kimi K2.6$0.164Fits in one request

GLM 5.2 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 5.2 and Kimi K2.6
SpecificationZ.ai GLM 5.2MoonshotAI Kimi K2.6
MakerZ.aiMoonshot AI
WeightsOpen weightsOpen weights
ReleasedJune 16, 2026April 20, 2026
Context window1.05M262K
Input $/Mtok$0.0341$0.65
Output $/Mtok$7.00$3.41
Coding index57.744.2
Independent measurements behind it11
Cost per solved task$0.86$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.2 better than Kimi K2.6 for coding?

Pick GLM 5.2 for coding: it scores 57.7 on the Vibe Coding Index against 44.2 for Kimi K2.6. Pick Kimi K2.6 when output tokens cost 2.1x less, or when a solved task costs $0.35 against $0.86.

Which is cheaper, GLM 5.2 or Kimi K2.6?

GLM 5.2 costs $0.0341 per million input tokens and $7.00 per million output tokens; Kimi K2.6 costs $0.65 and $3.41. Per solved SWE-bench Verified task, GLM 5.2 costs $0.86 and Kimi K2.6 $0.35.

Which has the bigger context window, GLM 5.2 or Kimi K2.6?

GLM 5.2, with 1.05M tokens against 262K.

How many benchmarks is the GLM 5.2 vs Kimi K2.6 comparison based on?

88 benchmarks have a result for both models as of October 21, 2026. GLM 5.2's coding index rests on 1 independent benchmark and Kimi K2.6's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next