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GLM 5.2 vs GPT-5.4 Nano

GLM 5.2 leads GPT-5.4 Nano on coding, 61.1 to 44.8 on the Vibe Coding Index, and GPT-5.4 Nano costs 3.5x less per output token ($1.25 vs $4.40 per million). Updated October 21, 2026; 69 benchmarks have a result for both.

Replace GLM 5.2 Replace GPT-5.4 Nano
GLM 5.2Z.ai
Coding
61.1
Overall
62.5
Output $/M
$4.40
64
GPT-5.4 NanoOpenAI
Coding
44.8
Overall
45.7
Output $/M
$1.25
5
vs boards won of 69 shared

GLM 5.2 or GPT-5.4 Nano: which to pick

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 44.8 for GPT-5.4 Nano.

Pick GPT-5.4 Nano for output tokens 3.5x cheaper ($1.25 vs $4.40 per million) and a lower cost per solved task ($0.14 against $0.86).

Model AGLM 5.2Z.ai61.1/1004 independent benchmarks$0.86 per solved taskModel BGPT-5.4 NanoOpenAI44.8/1002 independent benchmarks$0.14 per solved task
Shared results
69
GLM 5.2 only
29
GPT-5.4 Nano only
16
Like-for-like categories
7 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-5.4 Nano 44.8 from 2 benchmarks.
Widest category
Agentic work, 19.8 points apart on average over 5 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): GLM 5.2 64.0% against GPT-5.4 Nano 26.1%, 37.9 points apart on a 0 to 100 scale.
Output price
GLM 5.2 $4.40 against GPT-5.4 Nano $1.25 per million output tokens, 3.5x apart.
Context window
GLM 5.2 takes 1.05M tokens, GPT-5.4 Nano 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-5.4 NanoTies
Coding111
Intelligence20
Agentic work50
Reasoning111
Math51
Knowledge91
General211
All shared boards645
CodingLike-for-likeSix of these boards feed the Vibe Coding Index111
Coding benchmarks for GLM 5.2 and GPT-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
LMArena WebDev1604Not measuredOnly GLM 5.2 measured
AA Coding Index68.856.1GLM 5.2
LiveCodeBench (Vals AI)69.5%84.0%GPT-5.4 Nano
SWE-bench Verified (Vals AI)82.8%69.8%GLM 5.2
Vibe Code Bench (Vals AI)64.0%26.1%GLM 5.2
Code migration (Vals AI)37.9%14.5%GLM 5.2
ProgramBench (Vals AI)0.5%Not measuredOnly GLM 5.2 measured
Terminal-Bench 2.1 (Vals AI)67.8%41.6%GLM 5.2
SkillsBench (Vals AI)45.1%Not measuredOnly GLM 5.2 measured
SciCode51.2%47.2%GLM 5.2
Terminal-Bench Hard (Artificial Analysis run)50.8%42.4%GLM 5.2
FrontierCode24.5%Not measuredOnly GLM 5.2 measured
WeirdML70.1%49.2%GLM 5.2
ALE-Bench1047.01004.5GLM 5.2
LMArena Text: coding14871404GLM 5.2
LMArena Text: software and IT14861402GLM 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 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GLM 5.2 and GPT-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
AA Intelligence Index33.720.7GLM 5.2
Epoch Capabilities Index151.9146.0GLM 5.2
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
Agentic work benchmarks for GLM 5.2 and GPT-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
AA Agentic Index38.416.0GLM 5.2
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 apps1178Not 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%38.2%GLM 5.2
Tax Agent Bench (Vals AI)Not measured5.0%Only GPT-5.4 Nano measured
Legal Research Bench (Vals AI)31.3%6.3%GLM 5.2
Excel Modeling Benchmark (Vals AI)61.5%44.8%GLM 5.2
τ²-Bench Telecom99.1%76.0%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 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index111
Reasoning benchmarks for GLM 5.2 and GPT-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
GPQA Diamond85.6%77.5%GLM 5.2
MMMU Pro (Vals AI)Not measured73.6%Only GPT-5.4 Nano measured
GPQA Diamond (Artificial Analysis run)89.5%81.7%GLM 5.2
Humanity's Last Exam (Artificial Analysis run)41.1%28.3%GLM 5.2
GPQA Diamond (Epoch AI run)91.9%78.5%GLM 5.2
ARC-AGI77.0%51.5%GLM 5.2
ARC-AGI-222.8%5.7%GLM 5.2
SimpleBench58.8%Not measuredOnly GLM 5.2 measured
Chess puzzles22.0%45.0%GPT-5.4 Nano
Mystery game puzzles19.0%9.0%GLM 5.2
EBR-bench9.5%Not measuredOnly GLM 5.2 measured
LMArena Text: hard prompts14811381GLM 5.2
LMArena Text: expert14871396GLM 5.2
LMArena Text: hard prompts in English14811387GLM 5.2
LMArena Vision: diagramsNot measured1210Only GPT-5.4 Nano measured
LMArena Vision: homeworkNot measured1225Only GPT-5.4 Nano measured
Kagi LLM Benchmark62.6%39.7%GLM 5.2
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index51
Math benchmarks for GLM 5.2 and GPT-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
AIMENot measured88.8%Only GPT-5.4 Nano measured
OTIS Mock AIME86.4%87.8%GPT-5.4 Nano
FrontierMath, tiers 1 to 359.2%44.9%GLM 5.2
FrontierMath, tier 429.3%12.2%GLM 5.2
ProofBench35.0%5.0%GLM 5.2
LMArena Text: math14831405GLM 5.2
LMArena Text: mathematical work14891409GLM 5.2
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index91
Knowledge benchmarks for GLM 5.2 and GPT-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
MMLU Pro86.7%77.2%GLM 5.2
LegalBench (Vals AI)84.1%77.9%GLM 5.2
CaseLaw (Vals AI)Not measured51.9%Only GPT-5.4 Nano measured
CorpFin (Vals AI)66.1%61.2%GLM 5.2
TaxEval (Vals AI)73.3%67.4%GLM 5.2
MortgageTax (Vals AI)Not measured59.1%Only GPT-5.4 Nano measured
MedCode (Vals AI)40.8%41.0%GPT-5.4 Nano
SimpleQA Verified34.2%11.7%GLM 5.2
LMArena Text: science14891374GLM 5.2
LMArena Text: medicine and healthcare14751369GLM 5.2
LMArena Text: legal and government14861368GLM 5.2
LMArena Text: business and finance14511366GLM 5.2
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 5.2 and GPT-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
Design Arena: websites1285Not measuredOnly GLM 5.2 measured
Design Arena: UI components1296Not measuredOnly GLM 5.2 measured
Design Arena: game dev1268Not measuredOnly GLM 5.2 measured
Design Arena: data viz1285Not measuredOnly GLM 5.2 measured
Design Arena: 3D1288Not measuredOnly GLM 5.2 measured
Design Arena: all code categories1288Not measuredOnly GLM 5.2 measured
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 index211
General benchmarks for GLM 5.2 and GPT-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
SAGE (Vals AI)Not measured38.1%Only GPT-5.4 Nano measured
MedScribe (Vals AI)83.5%77.1%GLM 5.2
Vals Multimodal IndexNot measured47.6%Only GPT-5.4 Nano measured
IFBench73.3%75.9%GPT-5.4 Nano
Long context reasoning (AA-LCR)78.3%76.7%GLM 5.2
DTBench93.6%80.3%GLM 5.2
LMCA45.8%36.9%GLM 5.2
Surface Evolver Bench55.6%Not measuredOnly GLM 5.2 measured
LMArena Text14701372GLM 5.2
LMArena Text: instruction following14661362GLM 5.2
LMArena Text: creative writing14631315GLM 5.2
LMArena VisionNot measured1196Only GPT-5.4 Nano measured
LMArena Text: English14751381GLM 5.2
LMArena Text: non-English14591359GLM 5.2
LMArena Text: Chinese15221391GLM 5.2
LMArena Text: German14701368GLM 5.2
LMArena Text: Japanese14501343GLM 5.2
LMArena Text: Korean14401321GLM 5.2
LMArena Text: French14791395GLM 5.2
LMArena Text: Spanish14781371GLM 5.2
LMArena Text: Russian14681363GLM 5.2
LMArena Text: Polish14561366GLM 5.2
LMArena Text: multi-turn14691382GLM 5.2
LMArena Text: longer queries14801365GLM 5.2
LMArena Text: writing and language14631338GLM 5.2
LMArena Text: entertainment and media14501325GLM 5.2
LMArena Vision: EnglishNot measured1202Only GPT-5.4 Nano measured
LMArena Vision: ChineseNot measured1232Only GPT-5.4 Nano measured
LMArena Vision: reading textNot measured1204Only GPT-5.4 Nano measured
LMArena Vision: humorNot measured1161Only GPT-5.4 Nano measured
LMArena Vision: recognizing thingsNot measured1141Only GPT-5.4 Nano measured
LMArena Vision: creative writingNot measured1159Only GPT-5.4 Nano 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-5.4 Nano
BenchmarkGLM 5.2GPT-5.4 NanoLeader
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-5.4 Nano$0.0008Fits in one request

GPT-5.4 Nano costs less

Repository review

50K input + 3K output tokens

GLM 5.2$0.083Fits in one request
GPT-5.4 Nano$0.014Fits in one request

GPT-5.4 Nano costs less

Agent loop

200K input + 10K output tokens

GLM 5.2$0.324Fits in one request
GPT-5.4 Nano$0.052Fits in one request

GPT-5.4 Nano 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-5.4 Nano
SpecificationZ.ai GLM 5.2OpenAI GPT-5.4 Nano
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJune 16, 2026March 17, 2026
Context window1.05M400K
Input $/Mtok$1.40$0.20
Output $/Mtok$4.40$1.25
Coding index61.144.8
Independent measurements behind it42
Cost per solved task$0.86$0.14
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.2 better than GPT-5.4 Nano for coding?

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 44.8 for GPT-5.4 Nano. Pick GPT-5.4 Nano for output tokens 3.5x cheaper ($1.25 vs $4.40 per million) and a lower cost per solved task ($0.14 against $0.86).

Which is cheaper, GLM 5.2 or GPT-5.4 Nano?

GLM 5.2 costs $1.40 per million input tokens and $4.40 per million output tokens; GPT-5.4 Nano costs $0.20 and $1.25. Per solved SWE-bench Verified task, GLM 5.2 costs $0.86 and GPT-5.4 Nano $0.14.

Which has the bigger context window, GLM 5.2 or GPT-5.4 Nano?

GLM 5.2, with 1.05M tokens against 400K.

How many benchmarks is the GLM 5.2 vs GPT-5.4 Nano comparison based on?

69 benchmarks have a result for both models as of October 21, 2026. GLM 5.2's coding index rests on 4 independent benchmarks and GPT-5.4 Nano's on 2. Where only one model has a result, the page says so instead of naming a winner.

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