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GLM 5.2 vs GPT-5.2

GLM 5.2 leads GPT-5.2 on coding, 61.1 to 55.9 on the Vibe Coding Index, and GLM 5.2 costs 3.2x less per output token ($4.40 vs $14.00 per million). Updated October 22, 2026; 79 benchmarks have a result for both.

Replace GLM 5.2 Replace GPT-5.2
GLM 5.2Z.ai
Coding
61.1
Overall
62.5
Output $/M
$4.40
57
GPT-5.2OpenAI
Coding
55.9
Overall
60.7
Output $/M
$14.00
21
vs boards won of 79 shared, 1 tied

GLM 5.2 or GPT-5.2: which to pick

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 55.9 for GPT-5.2.

Pick GPT-5.2 for work measured by LiveCodeBench (Vals AI) or WeirdML, where it leads.

Model AGLM 5.2Z.ai61.1/1004 independent benchmarks$0.86 per solved taskModel BGPT-5.2OpenAI55.9/1003 independent benchmarks$1.91 per solved task
Shared results
79
GLM 5.2 only
19
GPT-5.2 only
35
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 5.2 61.1 from 4 benchmarks, GPT-5.2 55.9 from 3 benchmarks.
Widest category
Agentic work, 15.5 points apart on average over 7 shared benchmarks.
Widest single gap
ARC-AGI-2: GLM 5.2 22.8% against GPT-5.2 52.9%, 30.1 points apart on a 0 to 100 scale.
Output price
GLM 5.2 $4.40 against GPT-5.2 $14.00 per million output tokens, 3.2x apart.
Context window
GLM 5.2 takes 1.05M tokens, GPT-5.2 400K.

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 5.2BarsGPT-5.2Ties
Coding73
Intelligence11
Agentic work601 tie
Reasoning68
Math33
Knowledge73
Web design80
General193
All shared boards57211 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index73
Coding benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
SWE-bench VerifiedNot measured72.8%Only GPT-5.2 measured
SWE-bench MultilingualNot measured66.7%Only GPT-5.2 measured
LMArena WebDev16041417GLM 5.2
AA Coding Index68.8Not measuredOnly GLM 5.2 measured
LiveCodeBench (Vals AI)69.5%85.4%GPT-5.2
SWE-bench Verified (Vals AI)82.8%75.8%GLM 5.2
Vibe Code Bench (Vals AI)64.0%53.5%GLM 5.2
Code migration (Vals AI)37.9%Not measuredOnly GLM 5.2 measured
ProgramBench (Vals AI)0.5%Not measuredOnly GLM 5.2 measured
Terminal-Bench 2.1 (Vals AI)67.8%Not measuredOnly GLM 5.2 measured
SkillsBench (Vals AI)45.1%Not measuredOnly GLM 5.2 measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GPT-5.2 measured
SciCode51.2%Not measuredOnly GLM 5.2 measured
Terminal-Bench Hard (Artificial Analysis run)50.8%47.0%GLM 5.2
Terminal-BenchNot measured64.9%Only GPT-5.2 measured
FrontierCode24.5%Not measuredOnly GLM 5.2 measured
GSO-BenchNot measured27.5%Only GPT-5.2 measured
WeirdML70.1%72.2%GPT-5.2
ALE-Bench1047.01293.5GPT-5.2
LMArena Text: coding14871442GLM 5.2
LMArena Text: software and IT14861434GLM 5.2
LMArena WebDev: React1617Not measuredOnly GLM 5.2 measured
LMArena WebDev: HTML15651427GLM 5.2
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
AA Intelligence Index33.730.4GLM 5.2
Epoch Capabilities Index151.9153.7GPT-5.2
Agentic workLike-for-likePublic boards, shown as published, kept out of the index60
Agentic work benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
AA Agentic Index38.4Not measuredOnly GLM 5.2 measured
Design Arena: agents building web apps12221086GLM 5.2
Design Arena: agents building full-stack apps12411043GLM 5.2
Design Arena: agents building mobile apps11591093GLM 5.2
Design Arena: agents building Android apps11781059GLM 5.2
Design Arena: agents building Godot games11421142Tie
Design Arena: agents building games1206Not measuredOnly GLM 5.2 measured
Design Arena: HTML slides1125Not measuredOnly GLM 5.2 measured
Design Arena: PowerPoint slides1170Not measuredOnly GLM 5.2 measured
SREBench (Vals AI)0.0%Not measuredOnly GLM 5.2 measured
Finance Agent (Vals AI)49.7%Not measuredOnly GLM 5.2 measured
Legal Research Bench (Vals AI)31.3%Not measuredOnly GLM 5.2 measured
Excel Modeling Benchmark (Vals AI)61.5%Not measuredOnly GLM 5.2 measured
τ²-Bench Telecom99.1%84.8%GLM 5.2
APEX-Agents45.2%Not measuredOnly GLM 5.2 measured
METR time horizonsNot measured75.3%Only GPT-5.2 measured
Remote Labor IndexNot measured2.5%Only GPT-5.2 measured
GDPvalNot measured49.7%Only GPT-5.2 measured
DeepResearch BenchNot measured41.1%Only GPT-5.2 measured
PostTrainBench31.7%Not measuredOnly GLM 5.2 measured
Vending-Bench 2$8,314$3,591GLM 5.2
Berkeley Function Calling Leaderboard (BFCL)Not measured55.9%Only GPT-5.2 measured
Neither model has a result on the other 19 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index68
Reasoning benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
GPQA Diamond85.6%91.7%GPT-5.2
MMMU Pro (Vals AI)Not measured86.7%Only GPT-5.2 measured
GPQA Diamond (Artificial Analysis run)89.5%90.3%GPT-5.2
Humanity's Last Exam (Artificial Analysis run)41.1%37.7%GLM 5.2
GPQA Diamond (Epoch AI run)91.9%91.4%GLM 5.2
ARC-AGI77.0%86.2%GPT-5.2
ARC-AGI-222.8%52.9%GPT-5.2
SimpleBench58.8%45.8%GLM 5.2
Chess puzzles22.0%48.0%GPT-5.2
Mystery game puzzles19.0%23.0%GPT-5.2
EBR-bench9.5%23.0%GPT-5.2
VPCTNot measured84.0%Only GPT-5.2 measured
LMArena Text: hard prompts14811428GLM 5.2
LMArena Text: expert14871445GLM 5.2
LMArena Text: hard prompts in English14811431GLM 5.2
LMArena Vision: diagramsNot measured1265Only GPT-5.2 measured
LMArena Vision: homeworkNot measured1276Only GPT-5.2 measured
Kagi LLM Benchmark62.6%73.3%GPT-5.2
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index33
Math benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
AIMENot measured96.9%Only GPT-5.2 measured
MGSM (Vals AI)Not measured94.0%Only GPT-5.2 measured
AA Math IndexNot measured99.0Only GPT-5.2 measured
AIME 2025 (Artificial Analysis run)Not measured99.0%Only GPT-5.2 measured
OTIS Mock AIME86.4%96.1%GPT-5.2
FrontierMath, tiers 1 to 359.2%67.4%GPT-5.2
FrontierMath, tier 429.3%31.7%GPT-5.2
ProofBench35.0%15.0%GLM 5.2
LMArena Text: math14831440GLM 5.2
LMArena Text: mathematical work14891442GLM 5.2
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index73
Knowledge benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
MMLU Pro86.7%86.2%GLM 5.2
LegalBench (Vals AI)84.1%82.8%GLM 5.2
CaseLaw (Vals AI)Not measured66.0%Only GPT-5.2 measured
CorpFin (Vals AI)66.1%65.9%GLM 5.2
TaxEval (Vals AI)73.3%75.8%GPT-5.2
MortgageTax (Vals AI)Not measured67.1%Only GPT-5.2 measured
MedQA (Vals AI)Not measured94.1%Only GPT-5.2 measured
MedCode (Vals AI)40.8%49.8%GPT-5.2
MMLU Pro (Artificial Analysis run)Not measured87.4%Only GPT-5.2 measured
SimpleQA Verified34.2%37.1%GPT-5.2
LMArena Text: science14891425GLM 5.2
LMArena Text: medicine and healthcare14751425GLM 5.2
LMArena Text: legal and government14861427GLM 5.2
LMArena Text: business and finance14511414GLM 5.2
FACTS Benchmark SuiteNot measured48.5%Only GPT-5.2 measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
Design Arena: websites12851195GLM 5.2
Design Arena: UI components12941190GLM 5.2
Design Arena: game dev12681195GLM 5.2
Design Arena: data viz12851202GLM 5.2
Design Arena: 3D12871079GLM 5.2
Design Arena: all code categories12871170GLM 5.2
Design Arena: SVG12131139GLM 5.2
Design Arena: ASCII art11911152GLM 5.2
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index193
General benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
SAGE (Vals AI)Not measured49.3%Only GPT-5.2 measured
MedScribe (Vals AI)83.5%84.4%GPT-5.2
IFBench73.3%75.4%GPT-5.2
Long context reasoning (AA-LCR)78.3%82.7%GPT-5.2
DTBench93.6%90.9%GLM 5.2
LMCA45.8%43.9%GLM 5.2
CL-benchNot measured18.2%Only GPT-5.2 measured
Surface Evolver Bench55.6%Not measuredOnly GLM 5.2 measured
Furniture assemblyNot measured38.3%Only GPT-5.2 measured
LMArena Text14701416GLM 5.2
LMArena Text: instruction following14661409GLM 5.2
LMArena Text: creative writing14631376GLM 5.2
LMArena VisionNot measured1246Only GPT-5.2 measured
LMArena Text: English14751422GLM 5.2
LMArena Text: non-English14591405GLM 5.2
LMArena Text: Chinese15221447GLM 5.2
LMArena Text: German14701444GLM 5.2
LMArena Text: Japanese14501420GLM 5.2
LMArena Text: Korean14401374GLM 5.2
LMArena Text: French14791454GLM 5.2
LMArena Text: Spanish14781413GLM 5.2
LMArena Text: Russian14681415GLM 5.2
LMArena Text: Polish14561426GLM 5.2
LMArena Text: multi-turn14691419GLM 5.2
LMArena Text: longer queries14801413GLM 5.2
LMArena Text: writing and language14631392GLM 5.2
LMArena Text: entertainment and media14501378GLM 5.2
LMArena Vision: EnglishNot measured1243Only GPT-5.2 measured
LMArena Vision: ChineseNot measured1305Only GPT-5.2 measured
LMArena Vision: reading textNot measured1257Only GPT-5.2 measured
LMArena Vision: humorNot measured1227Only GPT-5.2 measured
LMArena Vision: captioningNot measured1267Only GPT-5.2 measured
LMArena Vision: recognizing thingsNot measured1232Only GPT-5.2 measured
LMArena Vision: creative writingNot measured1225Only GPT-5.2 measured
LMArena DocumentNot measured1405Only GPT-5.2 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.2 and GPT-5.2
BenchmarkGLM 5.2GPT-5.2Leader
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 5.2$0.0036Fits in one request
GPT-5.2$0.0088Fits in one request

GLM 5.2 costs less

Repository review

50K input + 3K output tokens

GLM 5.2$0.083Fits in one request
GPT-5.2$0.130Fits in one request

GLM 5.2 costs less

Agent loop

200K input + 10K output tokens

GLM 5.2$0.324Fits in one request
GPT-5.2$0.490Fits in one request

GLM 5.2 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 5.2 and GPT-5.2
SpecificationZ.ai GLM 5.2OpenAI GPT-5.2
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJune 16, 2026December 10, 2025
Context window1.05M400K
Input $/Mtok$1.40$1.75
Output $/Mtok$4.40$14.00
Coding index61.155.9
Independent measurements behind it43
Cost per solved task$0.86$1.91
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.2 better than GPT-5.2 for coding?

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 55.9 for GPT-5.2. Pick GPT-5.2 for work measured by LiveCodeBench (Vals AI) or WeirdML, where it leads.

Which is cheaper, GLM 5.2 or GPT-5.2?

GLM 5.2 costs $1.40 per million input tokens and $4.40 per million output tokens; GPT-5.2 costs $1.75 and $14.00. Per solved SWE-bench Verified task, GLM 5.2 costs $0.86 and GPT-5.2 $1.91.

Which has the bigger context window, GLM 5.2 or GPT-5.2?

GLM 5.2, with 1.05M tokens against 400K.

How many benchmarks is the GLM 5.2 vs GPT-5.2 comparison based on?

79 benchmarks have a result for both models as of October 22, 2026. GLM 5.2's coding index rests on 4 independent benchmarks and GPT-5.2's on 3. Where only one model has a result, the page says so instead of naming a winner.

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