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GLM 4.5V vs GLM 5

Updated October 21, 2026. 31 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 GLM 5
GLM 4.5VZ.ai
Coding
No data
Overall
7.6
Output $/M
$1.80
0
GLM 5Z.ai
Coding
41.7
Overall
27.9
Output $/M
$3.20
31
vs boards won of 31 shared

Decision reading

Only GLM 5 has a coding score, 41.7 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 1.8x less.

Model AGLM 4.5VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGLM 5Z.ai41.7/1003 independent benchmarks$0.63 per solved task
Shared results
31
GLM 4.5V only
9
GLM 5 only
44
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, GLM 5 41.7 from 3 benchmarks.
Widest category
Agentic work, 75.7 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5V 22.5% against GLM 5 98.2%, 75.7 points apart on a 0 to 100 scale.
Output price
GLM 4.5V $1.80 against GLM 5 $3.20 per million output tokens, 1.8x apart.
Context window
GLM 4.5V takes 66K tokens, GLM 5 205K.

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 4.5VBarsGLM 5Ties
Coding03
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge04
General015
All shared boards031
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.5V and GLM 5
BenchmarkGLM 4.5VGLM 5Leader
SWE-bench VerifiedNot measured72.8%Only GLM 5 measured
SWE-bench MultilingualNot measured69.7%Only GLM 5 measured
LMArena WebDevNot measured1435Only GLM 5 measured
LiveCodeBench (Vals AI)Not measured81.9%Only GLM 5 measured
SWE-bench Verified (Vals AI)Not measured71.4%Only GLM 5 measured
Vibe Code Bench (Vals AI)Not measured23.4%Only GLM 5 measured
LiveCodeBench (Artificial Analysis run)60.4%Not measuredOnly GLM 4.5V measured
Terminal-Bench Hard (Artificial Analysis run)6.8%43.2%GLM 5
Terminal-BenchNot measured52.4%Only GLM 5 measured
WeirdMLNot measured48.2%Only GLM 5 measured
ALE-BenchNot measured765.6Only GLM 5 measured
LMArena Text: coding13471461GLM 5
LMArena Text: software and IT13531460GLM 5
LMArena WebDev: ReactNot measured1424Only GLM 5 measured
LMArena WebDev: HTMLNot measured1450Only GLM 5 measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5V and GLM 5
BenchmarkGLM 4.5VGLM 5Leader
AA Intelligence Index7.627.9GLM 5
Epoch Capabilities IndexNot measured145.8Only GLM 5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5V and GLM 5
BenchmarkGLM 4.5VGLM 5Leader
Design Arena: agents building full-stack appsNot measured1123Only GLM 5 measured
Design Arena: agents building mobile appsNot measured1136Only GLM 5 measured
Design Arena: agents building Android appsNot measured1153Only GLM 5 measured
Design Arena: agents building Godot gamesNot measured1144Only GLM 5 measured
Design Arena: HTML slidesNot measured1148Only GLM 5 measured
τ²-Bench Telecom22.5%98.2%GLM 5
Vending-Bench 2Not measured$4,432Only GLM 5 measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for GLM 4.5V and GLM 5
BenchmarkGLM 4.5VGLM 5Leader
GPQA DiamondNot measured83.3%Only GLM 5 measured
GPQA Diamond (Artificial Analysis run)68.4%82.0%GLM 5
Humanity's Last Exam (Artificial Analysis run)6.3%29.3%GLM 5
GPQA Diamond (Epoch AI run)Not measured87.8%Only GLM 5 measured
ARC-AGINot measured44.7%Only GLM 5 measured
ARC-AGI-2Not measured4.9%Only GLM 5 measured
SimpleBenchNot measured53.2%Only GLM 5 measured
LMArena Text: hard prompts13351452GLM 5
LMArena Text: expert13531454GLM 5
LMArena Text: hard prompts in English13571460GLM 5
LMArena Vision: diagrams1151Not measuredOnly GLM 4.5V measured
LMArena Vision: homework1163Not measuredOnly GLM 4.5V measured
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 GLM 5
BenchmarkGLM 4.5VGLM 5Leader
AIMENot measured91.7%Only GLM 5 measured
AA Math Index73.0Not measuredOnly GLM 4.5V measured
AIME 2025 (Artificial Analysis run)73.0%Not measuredOnly GLM 4.5V measured
OTIS Mock AIMENot measured80.0%Only GLM 5 measured
LMArena Text: math13541440GLM 5
LMArena Text: mathematical work13361451GLM 5
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.5V and GLM 5
BenchmarkGLM 4.5VGLM 5Leader
MMLU ProNot measured86.0%Only GLM 5 measured
LegalBench (Vals AI)Not measured84.1%Only GLM 5 measured
CaseLaw (Vals AI)Not measured52.5%Only GLM 5 measured
CorpFin (Vals AI)Not measured62.9%Only GLM 5 measured
TaxEval (Vals AI)Not measured70.0%Only GLM 5 measured
MedQA (Vals AI)Not measured94.3%Only GLM 5 measured
MMLU Pro (Artificial Analysis run)78.8%Not measuredOnly GLM 4.5V measured
LMArena Text: science13301460GLM 5
LMArena Text: medicine and healthcare13491455GLM 5
LMArena Text: legal and government13381453GLM 5
LMArena Text: business and finance13091430GLM 5
Neither model has a result on the other 6 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 GLM 5
BenchmarkGLM 4.5VGLM 5Leader
Design Arena: websitesNot measured1247Only GLM 5 measured
Design Arena: UI componentsNot measured1230Only GLM 5 measured
Design Arena: game devNot measured1234Only GLM 5 measured
Design Arena: data vizNot measured1228Only GLM 5 measured
Design Arena: 3DNot measured1229Only GLM 5 measured
Design Arena: all code categoriesNot measured1246Only GLM 5 measured
Design Arena: SVGNot measured1168Only GLM 5 measured
Design Arena: ASCII artNot measured1146Only GLM 5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index015
General benchmarks for GLM 4.5V and GLM 5
BenchmarkGLM 4.5VGLM 5Leader
IFBench34.2%72.3%GLM 5
Long context reasoning (AA-LCR)0.0%75.7%GLM 5
CL-benchNot measured18.7%Only GLM 5 measured
LMArena Text13331446GLM 5
LMArena Text: instruction following13111428GLM 5
LMArena Text: creative writing12941438GLM 5
LMArena Vision1154Not measuredOnly GLM 4.5V measured
LMArena Text: English13621458GLM 5
LMArena Text: non-English13031430GLM 5
LMArena Text: Chinese13371511GLM 5
LMArena Text: GermanNot measured1447Only GLM 5 measured
LMArena Text: JapaneseNot measured1416Only GLM 5 measured
LMArena Text: KoreanNot measured1423Only GLM 5 measured
LMArena Text: FrenchNot measured1456Only GLM 5 measured
LMArena Text: Spanish13361454GLM 5
LMArena Text: Russian12981436GLM 5
LMArena Text: Polish13021434GLM 5
LMArena Text: multi-turn13331456GLM 5
LMArena Text: longer queries13051446GLM 5
LMArena Text: writing and language13021437GLM 5
LMArena Text: entertainment and media13031426GLM 5
LMArena Vision: English1183Not measuredOnly GLM 4.5V measured
LMArena Vision: reading text1151Not measuredOnly GLM 4.5V measured
Neither model has a result on the other 23 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 GLM 5
BenchmarkGLM 4.5VGLM 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
GLM 5$0.0026Fits in one request

GLM 4.5V costs less

Repository review

50K input + 3K output tokens

GLM 4.5V$0.035Fits in one request
GLM 5$0.060Fits in one request

GLM 4.5V costs less

Agent loop

200K input + 10K output tokens

GLM 4.5V$0.138Exceeds the context window
GLM 5$0.232Exceeds the context window

GLM 4.5V 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 GLM 5
SpecificationZ.ai GLM 4.5VZ.ai GLM 5
MakerZ.aiZ.ai
WeightsOpen weightsOpen weights
ReleasedAugust 11, 2025February 11, 2026
Context window66K205K
Input $/Mtok$0.60$1.00
Output $/Mtok$1.80$3.20
Coding indexNot benchmarked41.7
Independent measurements behind it03
Cost per solved taskNot computable$0.63
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5V better than GLM 5 for coding?

Only GLM 5 has a coding score, 41.7 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 1.8x less.

Which is cheaper, GLM 4.5V or GLM 5?

GLM 4.5V costs $0.60 per million input tokens and $1.80 per million output tokens; GLM 5 costs $1.00 and $3.20. Cost per solved task is known for GLM 5 only.

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

GLM 5, with 205K tokens against 66K.

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

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

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