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GLM 4.5 vs GLM 4.7

GLM 4.7 leads GLM 4.5 on the Artificial Analysis Intelligence Index, 22.2 to 12.8, at about the same output price ($2.20 vs $2.20 per million). Updated October 22, 2026; 56 benchmarks have a result for both.

Replace GLM 4.5 Replace GLM 4.7
GLM 4.5Z.ai
Coding
No data
Overall
No data
Output $/M
$2.20
9
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
47
vs boards won of 56 shared

GLM 4.5 or GLM 4.7: which to pick

Only GLM 4.7 has a coding score, 55.1 on the Vibe Coding Index; GLM 4.5 has none, so the two cannot be ranked on coding.

Pick GLM 4.5 for work measured by LMArena Text: expert or MGSM (Vals AI), where it leads.

Model AGLM 4.5Z.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved task
Shared results
56
GLM 4.5 only
5
GLM 4.7 only
25
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 4.5 not benchmarked, GLM 4.7 55.1 from 2 benchmarks.
Widest category
Agentic work, 52.9 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 43.0% against GLM 4.7 95.9%, 52.9 points apart on a 0 to 100 scale.
Output price
Both cost $2.20 per million output tokens.
Context window
GLM 4.5 takes 131K tokens, GLM 4.7 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 4.5BarsGLM 4.7Ties
Coding06
Intelligence01
Agentic work01
Reasoning15
Math33
Knowledge28
Web design07
General316
All shared boards947
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
Coding benchmarks for GLM 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
SWE-bench Verified64.2%Not measuredOnly GLM 4.5 measured
LMArena WebDevNot measured1435Only GLM 4.7 measured
AA Coding IndexNot measured45.3Only GLM 4.7 measured
LiveCodeBench (Vals AI)67.5%82.2%GLM 4.7
SWE-bench Verified (Vals AI)Not measured69.4%Only GLM 4.7 measured
LiveCodeBench (Artificial Analysis run)73.8%89.4%GLM 4.7
Terminal-Bench Hard (Artificial Analysis run)22.0%31.8%GLM 4.7
Terminal-BenchNot measured33.4%Only GLM 4.7 measured
WeirdML40.6%Not measuredOnly GLM 4.5 measured
ALE-Bench344.8399.5GLM 4.7
LMArena Text: coding14341454GLM 4.7
LMArena Text: software and IT14401453GLM 4.7
LMArena WebDev: ReactNot measured1420Only GLM 4.7 measured
LMArena WebDev: HTMLNot measured1447Only GLM 4.7 measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
AA Intelligence Index12.822.2GLM 4.7
Epoch Capabilities IndexNot measured143.6Only GLM 4.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
Design Arena: agents building full-stack appsNot measured1050Only GLM 4.7 measured
Design Arena: agents building mobile appsNot measured1105Only GLM 4.7 measured
Design Arena: agents building Android appsNot measured1112Only GLM 4.7 measured
Design Arena: agents building Godot gamesNot measured1058Only GLM 4.7 measured
τ²-Bench Telecom43.0%95.9%GLM 4.7
Vending-Bench 2Not measured$2,377Only GLM 4.7 measured
BrowseComp-PlusNot measured64.7%Only GLM 4.7 measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index15
Reasoning benchmarks for GLM 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
GPQA Diamond72.2%80.0%GLM 4.7
GPQA Diamond (Artificial Analysis run)78.2%85.9%GLM 4.7
Humanity's Last Exam (Artificial Analysis run)13.0%27.4%GLM 4.7
GPQA Diamond (Epoch AI run)Not measured83.3%Only GLM 4.7 measured
SimpleBenchNot measured47.7%Only GLM 4.7 measured
Chess puzzlesNot measured21.0%Only GLM 4.7 measured
LMArena Text: hard prompts14291443GLM 4.7
LMArena Text: expert14331424GLM 4.5
LMArena Text: hard prompts in English14291452GLM 4.7
Kagi LLM Benchmark57.9%Not measuredOnly GLM 4.5 measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index33
Math benchmarks for GLM 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
AIME86.7%93.3%GLM 4.7
MATH 500 (Vals AI)94.0%Not measuredOnly GLM 4.5 measured
MGSM (Vals AI)90.8%88.2%GLM 4.5
AA Math Index73.795.0GLM 4.7
AIME 2025 (Artificial Analysis run)73.7%95.0%GLM 4.7
OTIS Mock AIMENot measured83.3%Only GLM 4.7 measured
ProofBenchNot measured6.0%Only GLM 4.7 measured
LMArena Text: math14271424GLM 4.5
LMArena Text: mathematical work14301411GLM 4.5
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index28
Knowledge benchmarks for GLM 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
MMLU Pro81.2%82.7%GLM 4.7
LegalBench (Vals AI)75.6%83.4%GLM 4.7
CaseLaw (Vals AI)Not measured54.9%Only GLM 4.7 measured
CorpFin (Vals AI)61.0%46.4%GLM 4.5
TaxEval (Vals AI)72.4%68.8%GLM 4.5
MedQA (Vals AI)90.0%93.7%GLM 4.7
MedCode (Vals AI)Not measured32.8%Only GLM 4.7 measured
MMLU Pro (Artificial Analysis run)83.5%85.6%GLM 4.7
SimpleQA VerifiedNot measured32.2%Only GLM 4.7 measured
LMArena Text: science14441457GLM 4.7
LMArena Text: medicine and healthcare14551469GLM 4.7
LMArena Text: legal and government14381444GLM 4.7
LMArena Text: business and finance14201429GLM 4.7
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for GLM 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
Design Arena: websites11691225GLM 4.7
Design Arena: UI components11411196GLM 4.7
Design Arena: game dev11441188GLM 4.7
Design Arena: data viz11591195GLM 4.7
Design Arena: 3D11701190GLM 4.7
Design Arena: all code categories11651216GLM 4.7
Design Arena: SVG10961142GLM 4.7
Design Arena: ASCII artNot measured1165Only GLM 4.7 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index316
General benchmarks for GLM 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
MedScribe (Vals AI)Not measured68.6%Only GLM 4.7 measured
IFBench44.1%67.9%GLM 4.7
Long context reasoning (AA-LCR)52.7%71.0%GLM 4.7
Creative writing (Lech Mazur)73.4%Not measuredOnly GLM 4.5 measured
CL-benchNot measured15.9%Only GLM 4.7 measured
CL-bench LifeNot measured10.9%Only GLM 4.7 measured
LMArena Text14301435GLM 4.7
LMArena Text: instruction following14041412GLM 4.7
LMArena Text: creative writing13951401GLM 4.7
LMArena Text: English14371453GLM 4.7
LMArena Text: non-English14171417GLM 4.5
LMArena Text: Chinese14651495GLM 4.7
LMArena Text: German14071426GLM 4.7
LMArena Text: Japanese14151439GLM 4.7
LMArena Text: Korean13801399GLM 4.7
LMArena Text: French14181432GLM 4.7
LMArena Text: Spanish14541434GLM 4.5
LMArena Text: Russian14131423GLM 4.7
LMArena Text: Polish14221435GLM 4.7
LMArena Text: multi-turn14151446GLM 4.7
LMArena Text: longer queries14121432GLM 4.7
LMArena Text: writing and language14031411GLM 4.7
LMArena Text: entertainment and media14041400GLM 4.5
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 4.5 and GLM 4.7
BenchmarkGLM 4.5GLM 4.7Leader
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 4.5$0.0017Fits in one request
GLM 4.7$0.0017Fits in one request

Same cost

Repository review

50K input + 3K output tokens

GLM 4.5$0.037Fits in one request
GLM 4.7$0.037Fits in one request

Same cost

Agent loop

200K input + 10K output tokens

GLM 4.5$0.142Exceeds the context window
GLM 4.7$0.142Exceeds the context window

Same cost

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 4.5 and GLM 4.7
SpecificationZ.ai GLM 4.5Z.ai GLM 4.7
MakerZ.aiZ.ai
WeightsOpen weightsOpen weights
ReleasedJuly 25, 2025December 22, 2025
Context window131K205K
Input $/Mtok$0.60$0.60
Output $/Mtok$2.20$2.20
Coding indexNot benchmarked55.1
Independent measurements behind it02
Cost per solved taskNot computable$0.29
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 better than GLM 4.7 for coding?

Only GLM 4.7 has a coding score, 55.1 on the Vibe Coding Index; GLM 4.5 has none, so the two cannot be ranked on coding. Pick GLM 4.5 for work measured by LMArena Text: expert or MGSM (Vals AI), where it leads.

Which is cheaper, GLM 4.5 or GLM 4.7?

GLM 4.5 costs $0.60 per million input tokens and $2.20 per million output tokens; GLM 4.7 costs $0.60 and $2.20. Cost per solved task is known for GLM 4.7 only.

Which has the bigger context window, GLM 4.5 or GLM 4.7?

GLM 4.7, with 205K tokens against 131K.

How many benchmarks is the GLM 4.5 vs GLM 4.7 comparison based on?

56 benchmarks have a result for both models as of October 22, 2026. GLM 4.5's coding index rests on 0 independent benchmarks and GLM 4.7's on 2. Where only one model has a result, the page says so instead of naming a winner.

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