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GLM 4.7 vs GPT-4o (2024-05-13)

GLM 4.7 leads GPT-4o (2024-05-13) on the Artificial Analysis Intelligence Index, 22.2 to 7.3, and GLM 4.7 costs 6.8x less per output token ($2.20 vs $15.00 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

Replace GLM 4.7 Replace GPT-4o (2024-05-13)
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
37
GPT-4o (2024-05-13)OpenAI
Coding
No data
Overall
27.1
Output $/M
$15.00
0
vs boards won of 37 shared

GLM 4.7 or GPT-4o (2024-05-13): which to pick

Only GLM 4.7 has a coding score, 55.1 on the Vibe Coding Index; GPT-4o (2024-05-13) has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved taskModel BGPT-4o (2024-05-13)OpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
37
GLM 4.7 only
44
GPT-4o (2024-05-13) only
7
Like-for-like categories
6 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-4o (2024-05-13) not benchmarked.
Widest category
Math, 40.5 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: GLM 4.7 83.3% against GPT-4o (2024-05-13) 6.3%, 77.1 points apart on a 0 to 100 scale.
Output price
GLM 4.7 $2.20 against GPT-4o (2024-05-13) $15.00 per million output tokens, 6.8x apart.
Context window
GLM 4.7 takes 205K tokens, GPT-4o (2024-05-13) 128K.

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-4o (2024-05-13)Ties
Coding40
Intelligence10
Reasoning70
Math30
Knowledge50
General170
All shared boards370
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for GLM 4.7 and GPT-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
LMArena WebDev1435Not measuredOnly GLM 4.7 measured
AA Coding Index45.324.2GLM 4.7
LiveCodeBench (Vals AI)82.2%Not measuredOnly GLM 4.7 measured
SWE-bench Verified (Vals AI)69.4%Not measuredOnly GLM 4.7 measured
LiveCodeBench (Artificial Analysis run)89.4%33.4%GLM 4.7
Terminal-Bench Hard (Artificial Analysis run)31.8%Not measuredOnly GLM 4.7 measured
Terminal-Bench33.4%Not measuredOnly GLM 4.7 measured
ALE-Bench399.5Not measuredOnly GLM 4.7 measured
LMArena Text: coding14541297GLM 4.7
LMArena Text: software and IT14531297GLM 4.7
LMArena WebDev: React1420Not measuredOnly GLM 4.7 measured
LMArena WebDev: HTML1447Not measuredOnly GLM 4.7 measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.7 and GPT-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
AA Intelligence Index22.27.3GLM 4.7
Epoch Capabilities Index143.6Not measuredOnly GLM 4.7 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Agentic work benchmarks for GLM 4.7 and GPT-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
Design Arena: agents building full-stack apps1050Not measuredOnly GLM 4.7 measured
Design Arena: agents building mobile apps1105Not measuredOnly GLM 4.7 measured
Design Arena: agents building Android apps1112Not measuredOnly GLM 4.7 measured
Design Arena: agents building Godot games1058Not measuredOnly GLM 4.7 measured
τ²-Bench Telecom95.9%Not measuredOnly GLM 4.7 measured
METR time horizonsNot measured40.8%Only GPT-4o (2024-05-13) measured
BALROGNot measured32.3%Only GPT-4o (2024-05-13) measured
Vending-Bench 2$2,377Not measuredOnly GLM 4.7 measured
BrowseComp-Plus64.7%Not measuredOnly GLM 4.7 measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for GLM 4.7 and GPT-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
GPQA Diamond80.0%50.2%GLM 4.7
GPQA Diamond (Artificial Analysis run)85.9%52.6%GLM 4.7
Humanity's Last Exam (Artificial Analysis run)27.4%1.8%GLM 4.7
GPQA Diamond (Epoch AI run)83.3%48.9%GLM 4.7
SimpleBench47.7%Not measuredOnly GLM 4.7 measured
Chess puzzles21.0%Not measuredOnly GLM 4.7 measured
LMArena Text: hard prompts14431281GLM 4.7
LMArena Text: expert14241250GLM 4.7
LMArena Text: hard prompts in English14521293GLM 4.7
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for GLM 4.7 and GPT-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
AIME93.3%Not measuredOnly GLM 4.7 measured
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%6.3%GLM 4.7
ProofBench6.0%Not measuredOnly GLM 4.7 measured
MATH level 5Not measured51.0%Only GPT-4o (2024-05-13) measured
LMArena Text: math14241284GLM 4.7
LMArena Text: mathematical work14111284GLM 4.7
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for GLM 4.7 and GPT-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
MMLU Pro82.7%Not measuredOnly GLM 4.7 measured
LegalBench (Vals AI)83.4%Not measuredOnly GLM 4.7 measured
CaseLaw (Vals AI)54.9%Not measuredOnly GLM 4.7 measured
CorpFin (Vals AI)46.4%Not measuredOnly GLM 4.7 measured
TaxEval (Vals AI)68.8%Not measuredOnly GLM 4.7 measured
MedQA (Vals AI)93.7%Not measuredOnly GLM 4.7 measured
MedCode (Vals AI)32.8%Not measuredOnly GLM 4.7 measured
MMLU Pro (Artificial Analysis run)85.6%74.0%GLM 4.7
SimpleQA Verified32.2%Not measuredOnly GLM 4.7 measured
MMLUNot measured84.2%Only GPT-4o (2024-05-13) measured
LMArena Text: science14571295GLM 4.7
LMArena Text: medicine and healthcare14691278GLM 4.7
LMArena Text: legal and government14441314GLM 4.7
LMArena Text: business and finance14291262GLM 4.7
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 4.7 and GPT-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
Design Arena: websites1225Not measuredOnly GLM 4.7 measured
Design Arena: UI components1196Not measuredOnly GLM 4.7 measured
Design Arena: game dev1188Not measuredOnly GLM 4.7 measured
Design Arena: data viz1195Not measuredOnly GLM 4.7 measured
Design Arena: 3D1190Not measuredOnly GLM 4.7 measured
Design Arena: all code categories1216Not measuredOnly GLM 4.7 measured
Design Arena: SVG1142Not measuredOnly GLM 4.7 measured
Design Arena: ASCII art1165Not measuredOnly 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 index170
General benchmarks for GLM 4.7 and GPT-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
MedScribe (Vals AI)68.6%Not measuredOnly GLM 4.7 measured
IFBench67.9%Not measuredOnly GLM 4.7 measured
Long context reasoning (AA-LCR)71.0%Not measuredOnly GLM 4.7 measured
CL-bench15.9%Not measuredOnly GLM 4.7 measured
CL-bench Life10.9%Not measuredOnly GLM 4.7 measured
LMArena Text14351300GLM 4.7
LMArena Text: instruction following14121278GLM 4.7
LMArena Text: creative writing14011291GLM 4.7
LMArena VisionNot measured1137Only GPT-4o (2024-05-13) measured
LMArena Text: English14531312GLM 4.7
LMArena Text: non-English14171283GLM 4.7
LMArena Text: Chinese14951277GLM 4.7
LMArena Text: German14261283GLM 4.7
LMArena Text: Japanese14391257GLM 4.7
LMArena Text: Korean13991234GLM 4.7
LMArena Text: French14321304GLM 4.7
LMArena Text: Spanish14341292GLM 4.7
LMArena Text: Russian14231285GLM 4.7
LMArena Text: Polish14351365GLM 4.7
LMArena Text: multi-turn14461302GLM 4.7
LMArena Text: longer queries14321288GLM 4.7
LMArena Text: writing and language14111298GLM 4.7
LMArena Text: entertainment and media14001289GLM 4.7
LMArena Vision: EnglishNot measured1147Only GPT-4o (2024-05-13) measured
LMArena Vision: ChineseNot measured1132Only GPT-4o (2024-05-13) measured
Neither model has a result on the other 21 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-4o (2024-05-13)
BenchmarkGLM 4.7GPT-4o (2024-05-13)Leader
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-4o (2024-05-13)$0.013Fits in one request

GLM 4.7 costs less

Repository review

50K input + 3K output tokens

GLM 4.7$0.037Fits in one request
GPT-4o (2024-05-13)$0.295Fits in one request

GLM 4.7 costs less

Agent loop

200K input + 10K output tokens

GLM 4.7$0.142Exceeds the context window
GPT-4o (2024-05-13)$1.15Exceeds the context window

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-4o (2024-05-13)
SpecificationZ.ai GLM 4.7OpenAI GPT-4o (2024-05-13)
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 22, 2025May 13, 2024
Context window205K128K
Input $/Mtok$0.60$5.00
Output $/Mtok$2.20$15.00
Coding index55.1Not benchmarked
Independent measurements behind it20
Cost per solved task$0.29Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 better than GPT-4o (2024-05-13) for coding?

Only GLM 4.7 has a coding score, 55.1 on the Vibe Coding Index; GPT-4o (2024-05-13) has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GLM 4.7 or GPT-4o (2024-05-13)?

GLM 4.7 costs $0.60 per million input tokens and $2.20 per million output tokens; GPT-4o (2024-05-13) costs $5.00 and $15.00. Cost per solved task is known for GLM 4.7 only.

Which has the bigger context window, GLM 4.7 or GPT-4o (2024-05-13)?

GLM 4.7, with 205K tokens against 128K.

How many benchmarks is the GLM 4.7 vs GPT-4o (2024-05-13) comparison based on?

37 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-4o (2024-05-13)'s on 0. Where only one model has a result, the page says so instead of naming a winner.

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