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GLM 4.7 vs GPT-5.4

GPT-5.4 leads GLM 4.7 on coding, 64.4 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; 74 benchmarks have a result for both.

Replace GLM 4.7 Replace GPT-5.4
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
9
GPT-5.4OpenAI
Coding
64.4
Overall
69.6
Output $/M
$15.00
65
vs boards won of 74 shared

GLM 4.7 or GPT-5.4: which to pick

Pick GPT-5.4 for coding: it scores 64.4 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 $1.02).

Model AGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved taskModel BGPT-5.4OpenAI64.4/1003 independent benchmarks$1.02 per solved task
Shared results
74
GLM 4.7 only
7
GPT-5.4 only
36
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, GPT-5.4 64.4 from 3 benchmarks.
Widest category
Math, 18.5 points apart on average over 5 shared benchmarks.
Widest single gap
ProofBench: GLM 4.7 6.0% against GPT-5.4 56.0%, 50.0 points apart on a 0 to 100 scale.
Output price
GLM 4.7 $2.20 against GPT-5.4 $15.00 per million output tokens, 6.8x apart.
Context window
GLM 4.7 takes 205K tokens, GPT-5.4 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 4.7BarsGPT-5.4Ties
Coding011
Intelligence02
Agentic work42
Reasoning08
Math05
Knowledge111
Web design44
General022
All shared boards965
CodingLike-for-likeSix of these boards feed the Vibe Coding Index011
Coding benchmarks for GLM 4.7 and GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
LMArena WebDev14351464GPT-5.4
AA Coding Index45.371.1GPT-5.4
LiveCodeBench (Vals AI)82.2%84.1%GPT-5.4
SWE-bench Verified (Vals AI)69.4%78.2%GPT-5.4
Vibe Code Bench (Vals AI)Not measured67.4%Only GPT-5.4 measured
Code migration (Vals AI)Not measured35.0%Only GPT-5.4 measured
ProgramBench (Vals AI)Not measured0.5%Only GPT-5.4 measured
SkillsBench (Vals AI)Not measured51.7%Only GPT-5.4 measured
LiveCodeBench (Artificial Analysis run)89.4%Not measuredOnly GLM 4.7 measured
Terminal-Bench Hard (Artificial Analysis run)31.8%57.6%GPT-5.4
Terminal-Bench33.4%81.8%GPT-5.4
GSO-BenchNot measured31.4%Only GPT-5.4 measured
WeirdMLNot measured77.7%Only GPT-5.4 measured
MirrorCodeNot measured15.6%Only GPT-5.4 measured
ALE-Bench399.51607.0GPT-5.4
LMArena Text: coding14541496GPT-5.4
LMArena Text: software and IT14531491GPT-5.4
LMArena WebDev: React14201454GPT-5.4
LMArena WebDev: HTML14471478GPT-5.4
LMArena WebDev: from an imageNot measured1436Only GPT-5.4 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GLM 4.7 and GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
AA Intelligence Index22.239.0GPT-5.4
Epoch Capabilities Index143.6157.3GPT-5.4
Agentic workLike-for-likePublic boards, shown as published, kept out of the index42
Agentic work benchmarks for GLM 4.7 and GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
Design Arena: agents building web appsNot measured1059Only GPT-5.4 measured
Design Arena: agents building full-stack apps10501017GLM 4.7
Design Arena: agents building mobile apps11051087GLM 4.7
Design Arena: agents building Android apps11121031GLM 4.7
Design Arena: agents building Godot games10581135GPT-5.4
τ²-Bench Telecom95.9%87.1%GLM 4.7
APEX-AgentsNot measured52.4%Only GPT-5.4 measured
METR time horizonsNot measured74.3%Only GPT-5.4 measured
DeepResearch BenchNot measured35.1%Only GPT-5.4 measured
PostTrainBenchNot measured19.0%Only GPT-5.4 measured
Vending-Bench 2$2,377$6,144GPT-5.4
BrowseComp-Plus64.7%Not measuredOnly GLM 4.7 measured
Neither model has a result on the other 29 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for GLM 4.7 and GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
GPQA Diamond80.0%91.7%GPT-5.4
MMMU Pro (Vals AI)Not measured87.5%Only GPT-5.4 measured
GPQA Diamond (Artificial Analysis run)85.9%92.0%GPT-5.4
Humanity's Last Exam (Artificial Analysis run)27.4%43.7%GPT-5.4
GPQA Diamond (Epoch AI run)83.3%93.3%GPT-5.4
ARC-AGINot measured93.7%Only GPT-5.4 measured
ARC-AGI-2Not measured74.0%Only GPT-5.4 measured
SimpleBench47.7%Not measuredOnly GLM 4.7 measured
Chess puzzles21.0%48.0%GPT-5.4
Mystery game puzzlesNot measured37.0%Only GPT-5.4 measured
EBR-benchNot measured25.4%Only GPT-5.4 measured
LMArena Text: hard prompts14431485GPT-5.4
LMArena Text: expert14241507GPT-5.4
LMArena Text: hard prompts in English14521479GPT-5.4
LMArena Vision: diagramsNot measured1327Only GPT-5.4 measured
LMArena Vision: homeworkNot measured1336Only GPT-5.4 measured
Kagi LLM BenchmarkNot measured63.8%Only GPT-5.4 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index05
Math benchmarks for GLM 4.7 and GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
AIME93.3%96.7%GPT-5.4
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%97.8%GPT-5.4
FrontierMath, tiers 1 to 3Not measured78.6%Only GPT-5.4 measured
FrontierMath, tier 4Not measured49.0%Only GPT-5.4 measured
ProofBench6.0%56.0%GPT-5.4
LMArena Text: math14241488GPT-5.4
LMArena Text: mathematical work14111497GPT-5.4
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index111
Knowledge benchmarks for GLM 4.7 and GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
MMLU Pro82.7%87.5%GPT-5.4
LegalBench (Vals AI)83.4%86.0%GPT-5.4
CaseLaw (Vals AI)54.9%63.8%GPT-5.4
CorpFin (Vals AI)46.4%65.3%GPT-5.4
TaxEval (Vals AI)68.8%74.0%GPT-5.4
MortgageTax (Vals AI)Not measured68.3%Only GPT-5.4 measured
MedQA (Vals AI)93.7%96.1%GPT-5.4
MedCode (Vals AI)32.8%41.3%GPT-5.4
MMLU Pro (Artificial Analysis run)85.6%Not measuredOnly GLM 4.7 measured
SimpleQA Verified32.2%45.1%GPT-5.4
LMArena Text: science14571479GPT-5.4
LMArena Text: medicine and healthcare14691458GLM 4.7
LMArena Text: legal and government14441486GPT-5.4
LMArena Text: business and finance14291474GPT-5.4
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index44
Web design benchmarks for GLM 4.7 and GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
Design Arena: websites12251198GLM 4.7
Design Arena: UI components11961212GPT-5.4
Design Arena: game dev11881194GPT-5.4
Design Arena: data viz11951196GPT-5.4
Design Arena: 3D11901065GLM 4.7
Design Arena: all code categories12161179GLM 4.7
Design Arena: SVG11421141GLM 4.7
Design Arena: ASCII art11651188GPT-5.4
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index022
General benchmarks for GLM 4.7 and GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
SAGE (Vals AI)Not measured43.3%Only GPT-5.4 measured
MedScribe (Vals AI)68.6%77.5%GPT-5.4
IFBench67.9%73.9%GPT-5.4
Long context reasoning (AA-LCR)71.0%82.0%GPT-5.4
DTBenchNot measured94.4%Only GPT-5.4 measured
LMCANot measured52.0%Only GPT-5.4 measured
CL-bench15.9%27.9%GPT-5.4
Furniture assemblyNot measured37.5%Only GPT-5.4 measured
CL-bench Life10.9%21.7%GPT-5.4
LMArena Text14351469GPT-5.4
LMArena Text: instruction following14121469GPT-5.4
LMArena Text: creative writing14011439GPT-5.4
LMArena VisionNot measured1303Only GPT-5.4 measured
LMArena Text: English14531467GPT-5.4
LMArena Text: non-English14171465GPT-5.4
LMArena Text: Chinese14951520GPT-5.4
LMArena Text: German14261472GPT-5.4
LMArena Text: Japanese14391485GPT-5.4
LMArena Text: Korean13991449GPT-5.4
LMArena Text: French14321493GPT-5.4
LMArena Text: Spanish14341452GPT-5.4
LMArena Text: Russian14231480GPT-5.4
LMArena Text: Polish14351472GPT-5.4
LMArena Text: multi-turn14461482GPT-5.4
LMArena Text: longer queries14321473GPT-5.4
LMArena Text: writing and language14111458GPT-5.4
LMArena Text: entertainment and media14001438GPT-5.4
LMArena Vision: EnglishNot measured1301Only GPT-5.4 measured
LMArena Vision: ChineseNot measured1354Only GPT-5.4 measured
LMArena Vision: reading textNot measured1312Only GPT-5.4 measured
LMArena Vision: humorNot measured1284Only GPT-5.4 measured
LMArena Vision: recognizing thingsNot measured1251Only GPT-5.4 measured
LMArena Vision: creative writingNot measured1283Only GPT-5.4 measured
LMArena DocumentNot measured1471Only GPT-5.4 measured
Neither model has a result on the other 12 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 GPT-5.4
BenchmarkGLM 4.7GPT-5.4Leader
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
GPT-5.4$0.010Fits in one request

GLM 4.7 costs less

Repository review

50K input + 3K output tokens

GLM 4.7$0.037Fits in one request
GPT-5.4$0.170Fits in one request

GLM 4.7 costs less

Agent loop

200K input + 10K output tokens

GLM 4.7$0.142Exceeds the context window
GPT-5.4$0.650Fits 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 GPT-5.4
SpecificationZ.ai GLM 4.7OpenAI GPT-5.4
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 22, 2025March 5, 2026
Context window205K1.05M
Input $/Mtok$0.60$2.50
Output $/Mtok$2.20$15.00
Coding index55.164.4
Independent measurements behind it23
Cost per solved task$0.29$1.02
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 better than GPT-5.4 for coding?

Pick GPT-5.4 for coding: it scores 64.4 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 $1.02).

Which is cheaper, GLM 4.7 or GPT-5.4?

GLM 4.7 costs $0.60 per million input tokens and $2.20 per million output tokens; GPT-5.4 costs $2.50 and $15.00. Per solved SWE-bench Verified task, GLM 4.7 costs $0.29 and GPT-5.4 $1.02.

Which has the bigger context window, GLM 4.7 or GPT-5.4?

GPT-5.4, with 1.05M tokens against 205K.

How many benchmarks is the GLM 4.7 vs GPT-5.4 comparison based on?

74 benchmarks have a result for both models as of October 22, 2026. GLM 4.7's coding index rests on 2 independent benchmarks and GPT-5.4's on 3. Where only one model has a result, the page says so instead of naming a winner.

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