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GLM 5.2 vs GPT-4.1

Updated October 21, 2026. 60 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 5.2 Replace GPT-4.1
GLM 5.2Z.ai
Coding
57.7
Overall
33.7
Output $/M
$7.00
59
GPT-4.1OpenAI
Coding
46.5
Overall
12.7
Output $/M
$8.00
1
vs boards won of 60 shared

Decision reading

Pick GLM 5.2 for coding: it scores 57.7 on the Vibe Coding Index against 46.5 for GPT-4.1, though on 1 benchmark against 2.

Pick GPT-4.1 when a solved task costs $0.37 against $0.86, or when the benchmark that matters is TaxEval (Vals AI), where it leads.

Model AGLM 5.2Z.ai57.7/1001 independent benchmark$0.86 per solved taskModel BGPT-4.1OpenAI46.5/1002 independent benchmarks$0.37 per solved task
Shared results
60
GLM 5.2 only
37
GPT-4.1 only
27
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 57.7 from 1 benchmark, GPT-4.1 46.5 from 2 benchmarks.
Widest category
Agentic work, 52.0 points apart on average over 1 shared benchmark.
Widest single gap
ARC-AGI: GLM 5.2 77.0% against GPT-4.1 5.5%, 71.5 points apart on a 0 to 100 scale.
Output price
GLM 5.2 $7.00 against GPT-4.1 $8.00 per million output tokens, 1.1x apart.
Context window
GLM 5.2 takes 1.05M tokens, GPT-4.1 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 5.2BarsGPT-4.1Ties
Coding60
Intelligence20
Agentic work10
Reasoning110
Math40
Knowledge81
Web design60
General210
All shared boards591
CodingLike-for-likeFour of these boards feed the Vibe Coding Index60
Coding benchmarks for GLM 5.2 and GPT-4.1
BenchmarkGLM 5.2GPT-4.1Leader
Aider polyglotNot measured52.4%Only GPT-4.1 measured
SWE-bench VerifiedNot measured39.6%Only GPT-4.1 measured
SWE-bench MultimodalNot measured31.1%Only GPT-4.1 measured
LMArena WebDev1604Not measuredOnly GLM 5.2 measured
AA Coding Index68.8Not measuredOnly GLM 5.2 measured
LiveCodeBench (Vals AI)69.5%54.7%GLM 5.2
SWE-bench Verified (Vals AI)82.8%Not measuredOnly GLM 5.2 measured
Vibe Code Bench (Vals AI)64.0%Not measuredOnly GLM 5.2 measured
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 measured45.7%Only GPT-4.1 measured
SciCode51.2%Not measuredOnly GLM 5.2 measured
Terminal-Bench Hard (Artificial Analysis run)50.8%13.6%GLM 5.2
FrontierCode24.5%Not measuredOnly GLM 5.2 measured
WeirdML70.1%39.0%GLM 5.2
ALE-Bench1047.0558.1GLM 5.2
LMArena Text: coding14871390GLM 5.2
LMArena Text: software and IT14861391GLM 5.2
LMArena WebDev: React1617Not measuredOnly GLM 5.2 measured
LMArena WebDev: HTML1565Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GLM 5.2 and GPT-4.1
BenchmarkGLM 5.2GPT-4.1Leader
AA Intelligence Index33.712.7GLM 5.2
Epoch Capabilities Index151.9136.7GLM 5.2
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 5.2 and GPT-4.1
BenchmarkGLM 5.2GPT-4.1Leader
AA Agentic Index38.4Not measuredOnly GLM 5.2 measured
Design Arena: agents building web apps1222Not measuredOnly GLM 5.2 measured
Design Arena: agents building full-stack apps1241Not measuredOnly GLM 5.2 measured
Design Arena: agents building mobile apps1160Not measuredOnly GLM 5.2 measured
Design Arena: agents building Android apps1184Not measuredOnly GLM 5.2 measured
Design Arena: agents building Godot games1142Not measuredOnly GLM 5.2 measured
Design Arena: agents building games1206Not measuredOnly GLM 5.2 measured
Design Arena: HTML slides1175Not measuredOnly GLM 5.2 measured
Design Arena: PowerPoint slides1195Not 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%47.1%GLM 5.2
APEX-Agents45.2%Not measuredOnly GLM 5.2 measured
PostTrainBench31.7%Not measuredOnly GLM 5.2 measured
Vending-Bench 2$8,314Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index110
Reasoning benchmarks for GLM 5.2 and GPT-4.1
BenchmarkGLM 5.2GPT-4.1Leader
GPQA Diamond85.6%65.4%GLM 5.2
MMMU Pro (Vals AI)Not measured72.4%Only GPT-4.1 measured
GPQA Diamond (Artificial Analysis run)89.5%66.6%GLM 5.2
Humanity's Last Exam (Artificial Analysis run)41.1%4.2%GLM 5.2
GPQA Diamond (Epoch AI run)91.9%66.9%GLM 5.2
ARC-AGI77.0%5.5%GLM 5.2
ARC-AGI-222.8%0.4%GLM 5.2
SimpleBench58.8%27.0%GLM 5.2
Chess puzzles22.0%3.0%GLM 5.2
Mystery game puzzles19.0%Not measuredOnly GLM 5.2 measured
EBR-bench9.5%Not measuredOnly GLM 5.2 measured
LMArena Text: hard prompts14811384GLM 5.2
LMArena Text: expert14871364GLM 5.2
LMArena Text: hard prompts in English14811393GLM 5.2
LMArena Vision: diagramsNot measured1215Only GPT-4.1 measured
LMArena Vision: homeworkNot measured1248Only GPT-4.1 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for GLM 5.2 and GPT-4.1
BenchmarkGLM 5.2GPT-4.1Leader
AIMENot measured39.6%Only GPT-4.1 measured
MATH 500 (Vals AI)Not measured87.2%Only GPT-4.1 measured
MGSM (Vals AI)Not measured87.7%Only GPT-4.1 measured
AA Math IndexNot measured34.7Only GPT-4.1 measured
AIME 2025 (Artificial Analysis run)Not measured34.7%Only GPT-4.1 measured
OTIS Mock AIME86.4%38.3%GLM 5.2
FrontierMath, tiers 1 to 359.2%6.0%GLM 5.2
FrontierMath, tier 429.3%Not measuredOnly GLM 5.2 measured
ProofBench35.0%Not measuredOnly GLM 5.2 measured
MATH level 5Not measured83.0%Only GPT-4.1 measured
LMArena Text: math14831369GLM 5.2
LMArena Text: mathematical work14891360GLM 5.2
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index81
Knowledge benchmarks for GLM 5.2 and GPT-4.1
BenchmarkGLM 5.2GPT-4.1Leader
MMLU Pro86.7%80.5%GLM 5.2
LegalBench (Vals AI)84.1%83.1%GLM 5.2
CaseLaw (Vals AI)Not measured69.9%Only GPT-4.1 measured
CorpFin (Vals AI)66.1%63.0%GLM 5.2
TaxEval (Vals AI)73.3%75.1%GPT-4.1
MortgageTax (Vals AI)Not measured65.9%Only GPT-4.1 measured
MedQA (Vals AI)Not measured91.2%Only GPT-4.1 measured
MedCode (Vals AI)40.8%Not measuredOnly GLM 5.2 measured
MMLU Pro (Artificial Analysis run)Not measured80.6%Only GPT-4.1 measured
SimpleQA Verified34.2%31.1%GLM 5.2
GeoBenchNot measured72.0%Only GPT-4.1 measured
LMArena Text: science14891382GLM 5.2
LMArena Text: medicine and healthcare14751379GLM 5.2
LMArena Text: legal and government14861399GLM 5.2
LMArena Text: business and finance14511369GLM 5.2
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for GLM 5.2 and GPT-4.1
BenchmarkGLM 5.2GPT-4.1Leader
Design Arena: websites12851039GLM 5.2
Design Arena: UI components12961000GLM 5.2
Design Arena: game dev12681080GLM 5.2
Design Arena: data viz12851104GLM 5.2
Design Arena: 3D1288850GLM 5.2
Design Arena: all code categories12881026GLM 5.2
Design Arena: SVG1214Not measuredOnly GLM 5.2 measured
Design Arena: ASCII art1190Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index210
General benchmarks for GLM 5.2 and GPT-4.1
BenchmarkGLM 5.2GPT-4.1Leader
MedScribe (Vals AI)83.5%Not measuredOnly GLM 5.2 measured
IFBench73.3%43.0%GLM 5.2
Long context reasoning (AA-LCR)78.3%68.3%GLM 5.2
DTBench93.6%68.3%GLM 5.2
LMCA45.8%25.6%GLM 5.2
Fiction.LiveBenchNot measured63.9%Only GPT-4.1 measured
Surface Evolver Bench55.6%Not measuredOnly GLM 5.2 measured
LMArena Text14701383GLM 5.2
LMArena Text: instruction following14661367GLM 5.2
LMArena Text: creative writing14631363GLM 5.2
LMArena VisionNot measured1210Only GPT-4.1 measured
LMArena Text: English14751392GLM 5.2
LMArena Text: non-English14591370GLM 5.2
LMArena Text: Chinese15221382GLM 5.2
LMArena Text: German14701381GLM 5.2
LMArena Text: Japanese14501319GLM 5.2
LMArena Text: Korean14401338GLM 5.2
LMArena Text: French14791382GLM 5.2
LMArena Text: Spanish14781376GLM 5.2
LMArena Text: Russian14681377GLM 5.2
LMArena Text: Polish14561389GLM 5.2
LMArena Text: multi-turn14691397GLM 5.2
LMArena Text: longer queries14801385GLM 5.2
LMArena Text: writing and language14631371GLM 5.2
LMArena Text: entertainment and media14501365GLM 5.2
LMArena Vision: EnglishNot measured1209Only GPT-4.1 measured
LMArena Vision: ChineseNot measured1226Only GPT-4.1 measured
LMArena Vision: reading textNot measured1218Only GPT-4.1 measured
LMArena Vision: humorNot measured1196Only GPT-4.1 measured
LMArena Vision: captioningNot measured1207Only GPT-4.1 measured
LMArena Vision: recognizing thingsNot measured1208Only GPT-4.1 measured
LMArena Vision: creative writingNot measured1210Only GPT-4.1 measured
Neither model has a result on the other 14 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-4.1
BenchmarkGLM 5.2GPT-4.1Leader
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$0.0035Fits in one request
GPT-4.1$0.0060Fits in one request

GLM 5.2 costs less

Repository review

50K input + 3K output tokens

GLM 5.2$0.023Fits in one request
GPT-4.1$0.124Fits in one request

GLM 5.2 costs less

Agent loop

200K input + 10K output tokens

GLM 5.2$0.077Fits in one request
GPT-4.1$0.480Fits 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-4.1
SpecificationZ.ai GLM 5.2OpenAI GPT-4.1
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJune 16, 2026April 14, 2025
Context window1.05M1.05M
Input $/Mtok$0.0341$2.00
Output $/Mtok$7.00$8.00
Coding index57.746.5
Independent measurements behind it12
Cost per solved task$0.86$0.37
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.2 better than GPT-4.1 for coding?

Pick GLM 5.2 for coding: it scores 57.7 on the Vibe Coding Index against 46.5 for GPT-4.1, though on 1 benchmark against 2. Pick GPT-4.1 when a solved task costs $0.37 against $0.86, or when the benchmark that matters is TaxEval (Vals AI), where it leads.

Which is cheaper, GLM 5.2 or GPT-4.1?

GLM 5.2 costs $0.0341 per million input tokens and $7.00 per million output tokens; GPT-4.1 costs $2.00 and $8.00. Per solved SWE-bench Verified task, GLM 5.2 costs $0.86 and GPT-4.1 $0.37.

Which has the bigger context window, GLM 5.2 or GPT-4.1?

GLM 5.2, with 1.05M tokens against 1.05M.

How many benchmarks is the GLM 5.2 vs GPT-4.1 comparison based on?

60 benchmarks have a result for both models as of October 21, 2026. GLM 5.2's coding index rests on 1 independent benchmark and GPT-4.1's on 2. Where only one model has a result, the page says so instead of naming a winner.

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