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GLM 4.7 vs GPT-5.5

GPT-5.5 leads GLM 4.7 on coding, 71.3 to 55.1 on the Vibe Coding Index, and GLM 4.7 costs 13.6x less per output token ($2.20 vs $30.00 per million). Updated October 22, 2026; 72 benchmarks have a result for both.

Replace GLM 4.7 Replace GPT-5.5
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
2
GPT-5.5OpenAI
Coding
71.3
Overall
69.2
Output $/M
$30.00
70
vs boards won of 72 shared

GLM 4.7 or GPT-5.5: which to pick

Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 55.1 for GLM 4.7.

Pick GLM 4.7 for output tokens 13.6x cheaper ($2.20 vs $30.00 per million) and a lower cost per solved task ($0.29 against $1.65).

Model AGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved taskModel BGPT-5.5OpenAI71.3/1005 independent benchmarks$1.65 per solved task
Shared results
72
GLM 4.7 only
9
GPT-5.5 only
62
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-5.5 71.3 from 5 benchmarks.
Widest category
Coding, 21.1 points apart on average over 11 shared benchmarks.
Widest single gap
ALE-Bench: GLM 4.7 399.5 against GPT-5.5 1943.0, 51.5 points apart on a 0 to 100 scale.
Output price
GLM 4.7 $2.20 against GPT-5.5 $30.00 per million output tokens, 13.6x apart.
Context window
GLM 4.7 takes 205K tokens, GPT-5.5 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-5.5Ties
Coding011
Intelligence02
Agentic work15
Reasoning09
Math04
Knowledge110
Web design08
General021
All shared boards270
CodingLike-for-likeSix of these boards feed the Vibe Coding Index011
Coding benchmarks for GLM 4.7 and GPT-5.5
BenchmarkGLM 4.7GPT-5.5Leader
LiveBench codingNot measured85.1%Only GPT-5.5 measured
LMArena WebDev14351513GPT-5.5
AA Coding Index45.374.9GPT-5.5
LiveCodeBench (Vals AI)82.2%85.3%GPT-5.5
SWE-bench Verified (Vals AI)69.4%82.6%GPT-5.5
Vibe Code Bench (Vals AI)Not measured69.8%Only GPT-5.5 measured
Code migration (Vals AI)Not measured45.2%Only GPT-5.5 measured
ProgramBench (Vals AI)Not measured0.5%Only GPT-5.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured76.4%Only GPT-5.5 measured
SkillsBench (Vals AI)Not measured62.5%Only GPT-5.5 measured
LiveCodeBench (Artificial Analysis run)89.4%Not measuredOnly GLM 4.7 measured
SciCodeNot measured56.1%Only GPT-5.5 measured
Terminal-Bench Hard (Artificial Analysis run)31.8%60.6%GPT-5.5
Terminal-Bench33.4%84.7%GPT-5.5
FrontierCodeNot measured43.0%Only GPT-5.5 measured
GSO-BenchNot measured40.2%Only GPT-5.5 measured
WeirdMLNot measured84.9%Only GPT-5.5 measured
MirrorCodeNot measured10.0%Only GPT-5.5 measured
ALE-Bench399.51943.0GPT-5.5
LMArena Text: coding14541494GPT-5.5
LMArena Text: software and IT14531493GPT-5.5
LMArena WebDev: React14201506GPT-5.5
LMArena WebDev: HTML14471543GPT-5.5
LMArena WebDev: from an imageNot measured1532Only GPT-5.5 measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GLM 4.7 and GPT-5.5
BenchmarkGLM 4.7GPT-5.5Leader
AA Intelligence Index22.238.4GPT-5.5
Epoch Capabilities Index143.6159.7GPT-5.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index15
Agentic work benchmarks for GLM 4.7 and GPT-5.5
BenchmarkGLM 4.7GPT-5.5Leader
AA Agentic IndexNot measured36.4Only GPT-5.5 measured
Design Arena: agents building web appsNot measured1117Only GPT-5.5 measured
Design Arena: agents building full-stack apps10501089GPT-5.5
Design Arena: agents building mobile apps11051142GPT-5.5
Design Arena: agents building Android apps11131164GPT-5.5
Design Arena: agents building Godot games10581173GPT-5.5
Design Arena: agents building gamesNot measured1179Only GPT-5.5 measured
Design Arena: HTML slidesNot measured1017Only GPT-5.5 measured
Design Arena: PowerPoint slidesNot measured1085Only GPT-5.5 measured
LiveBench researchNot measured61.6%Only GPT-5.5 measured
LiveBench browserNot measured48.0%Only GPT-5.5 measured
LiveBench long agenticNot measured44.6%Only GPT-5.5 measured
SREBench (Vals AI)Not measured3.8%Only GPT-5.5 measured
Finance Agent (Vals AI)Not measured51.8%Only GPT-5.5 measured
Tax Agent Bench (Vals AI)Not measured21.8%Only GPT-5.5 measured
Legal Research Bench (Vals AI)Not measured40.4%Only GPT-5.5 measured
Excel Modeling Benchmark (Vals AI)Not measured64.5%Only GPT-5.5 measured
Time Horizon Index (Vals AI)Not measured8.3%Only GPT-5.5 measured
τ²-Bench Telecom95.9%93.9%GLM 4.7
APEX-AgentsNot measured55.1%Only GPT-5.5 measured
Remote Labor IndexNot measured6.3%Only GPT-5.5 measured
OSWorld 2.0Not measured13.0%Only GPT-5.5 measured
DeepResearch BenchNot measured54.0%Only GPT-5.5 measured
PostTrainBenchNot measured27.2%Only GPT-5.5 measured
Vending-Bench 2$2,377$7,524GPT-5.5
BrowseComp-Plus64.7%Not measuredOnly GLM 4.7 measured
Neither model has a result on the other 15 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for GLM 4.7 and GPT-5.5
BenchmarkGLM 4.7GPT-5.5Leader
GPQA Diamond80.0%93.2%GPT-5.5
LiveBench reasoningNot measured89.7%Only GPT-5.5 measured
MMMU Pro (Vals AI)Not measured88.3%Only GPT-5.5 measured
GPQA Diamond (Artificial Analysis run)85.9%93.5%GPT-5.5
Humanity's Last Exam (Artificial Analysis run)27.4%45.8%GPT-5.5
GPQA Diamond (Epoch AI run)83.3%90.7%GPT-5.5
ARC-AGINot measured95.0%Only GPT-5.5 measured
ARC-AGI-2Not measured85.0%Only GPT-5.5 measured
SimpleBench47.7%69.0%GPT-5.5
Chess puzzles21.0%63.0%GPT-5.5
Mystery game puzzlesNot measured56.0%Only GPT-5.5 measured
EBR-benchNot measured34.3%Only GPT-5.5 measured
LMArena Text: hard prompts14431489GPT-5.5
LMArena Text: expert14241507GPT-5.5
LMArena Text: hard prompts in English14521483GPT-5.5
LMArena Vision: diagramsNot measured1325Only GPT-5.5 measured
LMArena Vision: homeworkNot measured1332Only GPT-5.5 measured
Kagi LLM BenchmarkNot measured88.8%Only GPT-5.5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GLM 4.7 and GPT-5.5
BenchmarkGLM 4.7GPT-5.5Leader
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%84.4%GPT-5.5
FrontierMath, tiers 1 to 3Not measured85.3%Only GPT-5.5 measured
FrontierMath, tier 4Not measured72.5%Only GPT-5.5 measured
ProofBench6.0%50.0%GPT-5.5
LMArena Text: math14241487GPT-5.5
LMArena Text: mathematical work14111496GPT-5.5
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index110
Knowledge benchmarks for GLM 4.7 and GPT-5.5
BenchmarkGLM 4.7GPT-5.5Leader
MMLU Pro82.7%88.1%GPT-5.5
LegalBench (Vals AI)83.4%86.5%GPT-5.5
CaseLaw (Vals AI)54.9%66.2%GPT-5.5
CorpFin (Vals AI)46.4%68.4%GPT-5.5
TaxEval (Vals AI)68.8%75.0%GPT-5.5
MortgageTax (Vals AI)Not measured68.8%Only GPT-5.5 measured
MedQA (Vals AI)93.7%Not measuredOnly GLM 4.7 measured
MedCode (Vals AI)32.8%49.1%GPT-5.5
MMLU Pro (Artificial Analysis run)85.6%Not measuredOnly GLM 4.7 measured
SimpleQA Verified32.2%63.0%GPT-5.5
LMArena Text: science14571485GPT-5.5
LMArena Text: medicine and healthcare14691465GLM 4.7
LMArena Text: legal and government14441491GPT-5.5
LMArena Text: business and finance14291478GPT-5.5
FACTS Benchmark SuiteNot measured66.7%Only GPT-5.5 measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for GLM 4.7 and GPT-5.5
BenchmarkGLM 4.7GPT-5.5Leader
Design Arena: websites12251256GPT-5.5
Design Arena: UI components11971257GPT-5.5
Design Arena: game dev11881293GPT-5.5
Design Arena: data viz11961264GPT-5.5
Design Arena: 3D11901197GPT-5.5
Design Arena: all code categories12161259GPT-5.5
Design Arena: SVG11421234GPT-5.5
Design Arena: ASCII art11651255GPT-5.5
LiveBench designNot measured70.3%Only GPT-5.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
General benchmarks for GLM 4.7 and GPT-5.5
BenchmarkGLM 4.7GPT-5.5Leader
LiveBench data analysisNot measured81.6%Only GPT-5.5 measured
Public Benefits Bench (Vals AI)Not measured60.9%Only GPT-5.5 measured
SAGE (Vals AI)Not measured51.5%Only GPT-5.5 measured
MedScribe (Vals AI)68.6%86.9%GPT-5.5
Vals Multimodal IndexNot measured68.1%Only GPT-5.5 measured
IFBench67.9%75.9%GPT-5.5
Long context reasoning (AA-LCR)71.0%84.3%GPT-5.5
DTBenchNot measured96.0%Only GPT-5.5 measured
LMCANot measured54.3%Only GPT-5.5 measured
CL-bench15.9%Not measuredOnly GLM 4.7 measured
Surface Evolver BenchNot measured88.1%Only GPT-5.5 measured
Furniture assemblyNot measured44.2%Only GPT-5.5 measured
ExploitBenchNot measured47.4%Only GPT-5.5 measured
CL-bench Life10.9%22.2%GPT-5.5
LMArena Text14351471GPT-5.5
LMArena Text: instruction following14121478GPT-5.5
LMArena Text: creative writing14011455GPT-5.5
LMArena VisionNot measured1297Only GPT-5.5 measured
LMArena Text: English14531470GPT-5.5
LMArena Text: non-English14171467GPT-5.5
LMArena Text: Chinese14951534GPT-5.5
LMArena Text: German14261480GPT-5.5
LMArena Text: Japanese14391499GPT-5.5
LMArena Text: Korean13991460GPT-5.5
LMArena Text: French14321485GPT-5.5
LMArena Text: Spanish14341468GPT-5.5
LMArena Text: Russian14231473GPT-5.5
LMArena Text: Polish14351465GPT-5.5
LMArena Text: multi-turn14461476GPT-5.5
LMArena Text: longer queries14321484GPT-5.5
LMArena Text: writing and language14111466GPT-5.5
LMArena Text: entertainment and media14001449GPT-5.5
LMArena Vision: EnglishNot measured1292Only GPT-5.5 measured
LMArena Vision: ChineseNot measured1360Only GPT-5.5 measured
LMArena Vision: reading textNot measured1306Only GPT-5.5 measured
LMArena Vision: humorNot measured1293Only GPT-5.5 measured
LMArena Vision: recognizing thingsNot measured1231Only GPT-5.5 measured
LMArena Vision: creative writingNot measured1301Only GPT-5.5 measured
LMArena DocumentNot measured1486Only GPT-5.5 measured
Neither model has a result on the other 7 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-5.5
BenchmarkGLM 4.7GPT-5.5Leader
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 4.7$0.0017Fits in one request
GPT-5.5$0.020Fits in one request

GLM 4.7 costs less

Repository review

50K input + 3K output tokens

GLM 4.7$0.037Fits in one request
GPT-5.5$0.340Fits in one request

GLM 4.7 costs less

Agent loop

200K input + 10K output tokens

GLM 4.7$0.142Exceeds the context window
GPT-5.5$1.30Fits 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-5.5
SpecificationZ.ai GLM 4.7OpenAI GPT-5.5
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedDecember 22, 2025April 24, 2026
Context window205K1.05M
Input $/Mtok$0.60$5.00
Output $/Mtok$2.20$30.00
Coding index55.171.3
Independent measurements behind it25
Cost per solved task$0.29$1.65
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 better than GPT-5.5 for coding?

Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 55.1 for GLM 4.7. Pick GLM 4.7 for output tokens 13.6x cheaper ($2.20 vs $30.00 per million) and a lower cost per solved task ($0.29 against $1.65).

Which is cheaper, GLM 4.7 or GPT-5.5?

GLM 4.7 costs $0.60 per million input tokens and $2.20 per million output tokens; GPT-5.5 costs $5.00 and $30.00. Per solved SWE-bench Verified task, GLM 4.7 costs $0.29 and GPT-5.5 $1.65.

Which has the bigger context window, GLM 4.7 or GPT-5.5?

GPT-5.5, with 1.05M tokens against 205K.

How many benchmarks is the GLM 4.7 vs GPT-5.5 comparison based on?

72 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-5.5's on 5. Where only one model has a result, the page says so instead of naming a winner.

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