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GLM 4.5V vs Kimi K2.5

Updated October 21, 2026. 36 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 4.5V Replace Kimi K2.5
GLM 4.5VZ.ai
Coding
No data
Overall
7.6
Output $/M
$1.80
0
Kimi K2.5Moonshot AI
Coding
38.6
Overall
23.5
Output $/M
$2.85
36
vs boards won of 36 shared

Decision reading

Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; GLM 4.5V has none, so the two cannot be ranked on coding.

GLM 4.5V has the edge where output tokens cost 1.6x less.

Model AGLM 4.5VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BKimi K2.5Moonshot AI38.6/1003 independent benchmarks$0.24 per solved task
Shared results
36
GLM 4.5V only
4
Kimi K2.5 only
62
Like-for-like categories
7 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 4.5V not benchmarked, Kimi K2.5 38.6 from 3 benchmarks.
Widest category
Agentic work, 73.4 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): GLM 4.5V 0.0% against Kimi K2.5 78.0%, 78.0 points apart on a 0 to 100 scale.
Output price
GLM 4.5V $1.80 against Kimi K2.5 $2.85 per million output tokens, 1.6x apart.
Context window
GLM 4.5V takes 66K tokens, Kimi K2.5 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 4.5VBarsKimi K2.5Ties
Coding03
Intelligence01
Agentic work01
Reasoning07
Math02
Knowledge04
General018
All shared boards036
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
SWE-bench VerifiedNot measured70.8%Only Kimi K2.5 measured
SWE-bench MultilingualNot measured67.3%Only Kimi K2.5 measured
LMArena WebDevNot measured1437Only Kimi K2.5 measured
AA Coding IndexNot measured46.8Only Kimi K2.5 measured
LiveCodeBench (Vals AI)Not measured83.9%Only Kimi K2.5 measured
SWE-bench Verified (Vals AI)Not measured70.0%Only Kimi K2.5 measured
Vibe Code Bench (Vals AI)Not measured17.5%Only Kimi K2.5 measured
Code migration (Vals AI)Not measured7.0%Only Kimi K2.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured42.0%Only Kimi K2.5 measured
LiveCodeBench (Artificial Analysis run)60.4%Not measuredOnly GLM 4.5V measured
Terminal-Bench Hard (Artificial Analysis run)6.8%34.8%Kimi K2.5
Terminal-BenchNot measured43.2%Only Kimi K2.5 measured
WeirdMLNot measured45.6%Only Kimi K2.5 measured
ALE-BenchNot measured821.6Only Kimi K2.5 measured
LMArena Text: coding13471483Kimi K2.5
LMArena Text: software and IT13531471Kimi K2.5
LMArena WebDev: ReactNot measured1429Only Kimi K2.5 measured
LMArena WebDev: HTMLNot measured1426Only Kimi K2.5 measured
LMArena WebDev: from an imageNot measured1439Only Kimi K2.5 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 GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
AA Intelligence Index7.623.5Kimi K2.5
Epoch Capabilities IndexNot measured148.1Only Kimi K2.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
Design Arena: agents building web appsNot measured1136Only Kimi K2.5 measured
Design Arena: agents building full-stack appsNot measured1114Only Kimi K2.5 measured
Design Arena: agents building mobile appsNot measured1147Only Kimi K2.5 measured
Design Arena: agents building Android appsNot measured1125Only Kimi K2.5 measured
Design Arena: agents building Godot gamesNot measured1219Only Kimi K2.5 measured
Finance Agent (Vals AI)Not measured35.8%Only Kimi K2.5 measured
Legal Research Bench (Vals AI)Not measured15.9%Only Kimi K2.5 measured
Excel Modeling Benchmark (Vals AI)Not measured28.5%Only Kimi K2.5 measured
τ²-Bench Telecom22.5%95.9%Kimi K2.5
OSWorldNot measured63.3%Only Kimi K2.5 measured
Vending-Bench 2Not measured$1,198Only Kimi K2.5 measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
GPQA DiamondNot measured84.1%Only Kimi K2.5 measured
MMMU Pro (Vals AI)Not measured84.3%Only Kimi K2.5 measured
GPQA Diamond (Artificial Analysis run)68.4%87.9%Kimi K2.5
Humanity's Last Exam (Artificial Analysis run)6.3%30.7%Kimi K2.5
ARC-AGINot measured65.3%Only Kimi K2.5 measured
ARC-AGI-2Not measured11.8%Only Kimi K2.5 measured
SimpleBenchNot measured46.8%Only Kimi K2.5 measured
LMArena Text: hard prompts13351453Kimi K2.5
LMArena Text: expert13531466Kimi K2.5
LMArena Text: hard prompts in English13571460Kimi K2.5
LMArena Vision: diagrams11511282Kimi K2.5
LMArena Vision: homework11631297Kimi K2.5
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
AIMENot measured95.6%Only Kimi K2.5 measured
AA Math Index73.0Not measuredOnly GLM 4.5V measured
AIME 2025 (Artificial Analysis run)73.0%Not measuredOnly GLM 4.5V measured
LMArena Text: math13541470Kimi K2.5
LMArena Text: mathematical work13361473Kimi K2.5
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
MMLU ProNot measured85.9%Only Kimi K2.5 measured
CaseLaw (Vals AI)Not measured58.7%Only Kimi K2.5 measured
CorpFin (Vals AI)Not measured68.3%Only Kimi K2.5 measured
TaxEval (Vals AI)Not measured74.2%Only Kimi K2.5 measured
MortgageTax (Vals AI)Not measured66.5%Only Kimi K2.5 measured
MedQA (Vals AI)Not measured94.4%Only Kimi K2.5 measured
MedCode (Vals AI)Not measured39.3%Only Kimi K2.5 measured
MMLU Pro (Artificial Analysis run)78.8%Not measuredOnly GLM 4.5V measured
SimpleQA VerifiedNot measured34.3%Only Kimi K2.5 measured
LMArena Text: science13301459Kimi K2.5
LMArena Text: medicine and healthcare13491448Kimi K2.5
LMArena Text: legal and government13381441Kimi K2.5
LMArena Text: business and finance13091427Kimi K2.5
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
Design Arena: websitesNot measured1249Only Kimi K2.5 measured
Design Arena: UI componentsNot measured1236Only Kimi K2.5 measured
Design Arena: game devNot measured1207Only Kimi K2.5 measured
Design Arena: data vizNot measured1218Only Kimi K2.5 measured
Design Arena: 3DNot measured1205Only Kimi K2.5 measured
Design Arena: all code categoriesNot measured1236Only Kimi K2.5 measured
Design Arena: SVGNot measured1149Only Kimi K2.5 measured
Design Arena: ASCII artNot measured1165Only Kimi K2.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
SAGE (Vals AI)Not measured49.9%Only Kimi K2.5 measured
MedScribe (Vals AI)Not measured76.4%Only Kimi K2.5 measured
IFBench34.2%70.2%Kimi K2.5
Long context reasoning (AA-LCR)0.0%78.0%Kimi K2.5
Fiction.LiveBenchNot measured86.1%Only Kimi K2.5 measured
CL-benchNot measured19.3%Only Kimi K2.5 measured
CL-bench LifeNot measured13.2%Only Kimi K2.5 measured
LMArena Text13331445Kimi K2.5
LMArena Text: instruction following13111431Kimi K2.5
LMArena Text: creative writing12941422Kimi K2.5
LMArena Vision11541269Kimi K2.5
LMArena Text: English13621453Kimi K2.5
LMArena Text: non-English13031433Kimi K2.5
LMArena Text: Chinese13371494Kimi K2.5
LMArena Text: GermanNot measured1441Only Kimi K2.5 measured
LMArena Text: JapaneseNot measured1423Only Kimi K2.5 measured
LMArena Text: KoreanNot measured1412Only Kimi K2.5 measured
LMArena Text: FrenchNot measured1454Only Kimi K2.5 measured
LMArena Text: Spanish13361450Kimi K2.5
LMArena Text: Russian12981435Kimi K2.5
LMArena Text: Polish13021445Kimi K2.5
LMArena Text: multi-turn13331444Kimi K2.5
LMArena Text: longer queries13051445Kimi K2.5
LMArena Text: writing and language13021425Kimi K2.5
LMArena Text: entertainment and media13031417Kimi K2.5
LMArena Vision: English11831274Kimi K2.5
LMArena Vision: ChineseNot measured1328Only Kimi K2.5 measured
LMArena Vision: reading text11511276Kimi K2.5
LMArena Vision: humorNot measured1284Only Kimi K2.5 measured
LMArena Vision: captioningNot measured1257Only Kimi K2.5 measured
LMArena Vision: recognizing thingsNot measured1285Only Kimi K2.5 measured
LMArena Vision: creative writingNot measured1269Only Kimi K2.5 measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.5V and Kimi K2.5
BenchmarkGLM 4.5VKimi K2.5Leader
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 4.5V$0.0015Fits in one request
Kimi K2.5$0.0020Fits in one request

GLM 4.5V costs less

Repository review

50K input + 3K output tokens

GLM 4.5V$0.035Fits in one request
Kimi K2.5$0.035Fits in one request

Kimi K2.5 costs less

Agent loop

200K input + 10K output tokens

GLM 4.5V$0.138Exceeds the context window
Kimi K2.5$0.135Fits in one request

Kimi K2.5 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 4.5V and Kimi K2.5
SpecificationZ.ai GLM 4.5VMoonshotAI Kimi K2.5
MakerZ.aiMoonshot AI
WeightsOpen weightsOpen weights
ReleasedAugust 11, 2025January 27, 2026
Context window66K262K
Input $/Mtok$0.60$0.532
Output $/Mtok$1.80$2.85
Coding indexNot benchmarked38.6
Independent measurements behind it03
Cost per solved taskNot computable$0.24
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5V better than Kimi K2.5 for coding?

Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; GLM 4.5V has none, so the two cannot be ranked on coding. GLM 4.5V has the edge where output tokens cost 1.6x less.

Which is cheaper, GLM 4.5V or Kimi K2.5?

GLM 4.5V costs $0.60 per million input tokens and $1.80 per million output tokens; Kimi K2.5 costs $0.532 and $2.85. Cost per solved task is known for Kimi K2.5 only.

Which has the bigger context window, GLM 4.5V or Kimi K2.5?

Kimi K2.5, with 262K tokens against 66K.

How many benchmarks is the GLM 4.5V vs Kimi K2.5 comparison based on?

36 benchmarks have a result for both models as of October 21, 2026. GLM 4.5V's coding index rests on 0 independent benchmarks and Kimi K2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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