GLM 5.3 Flash vs GPT-5.4 Nano

GLM 5.3 Flash leads GPT-5.4 Nano on coding, 57.7 to 44.8 on the Vibe Coding Index, and GLM 5.3 Flash costs 2.5x less per output token ($0.50 vs $1.25 per million). Updated October 22, 2026; 69 benchmarks have a result for both.

Replace GLM 5.3 Flash Replace GPT-5.4 Nano

GLM 5.3 FlashZ.ai

Coding: 57.7
Overall: 66.0
Output $/M: $0.50

GPT-5.4 NanoOpenAI

Coding: 44.8
Overall: 45.7
Output $/M: $1.25

vs boards won of 69 shared

GLM 5.3 Flash or GPT-5.4 Nano: which to pick

Pick GLM 5.3 Flash for coding: it scores 57.7 on the Vibe Coding Index against 44.8 for GPT-5.4 Nano.

Pick GPT-5.4 Nano for work measured by LiveCodeBench (Vals AI) or ALE-Bench, where it leads.

Model AGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved task Model BGPT-5.4 NanoOpenAI44.8/1002 independent benchmarks$0.14 per solved task

693316

Shared results: 69
GLM 5.3 Flash only: 33
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.

Coding
Vibe Coding Index, six public coding benchmarks
GLM 5.3 Flash
GLM 5.3 Flash scores 57.7 against 44.8.
6 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 41.8 against 20.7.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3 Flash
GLM 5.3 Flash leads, 50.9 against 16.0.
Same board, both measured
Reasoning
GPQA Diamond
GLM 5.3 Flash
GLM 5.3 Flash leads, 86.4% against 77.5%.
Same board, both measured
Math
AIME
No call
Only GPT-5.4 Nano has a AIME result, 88.8%.
Directional only
Knowledge
MMLU Pro
GLM 5.3 Flash
GLM 5.3 Flash leads, 86.1% against 77.2%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GLM 5.3 Flash has a Design Arena: websites result, 1272.
Directional only
General
Vals Index
No call
Only GLM 5.3 Flash has a Vals Index result, 50.9%.
Directional only
Long documents
Listed context window
GLM 5.3 Flash
GLM 5.3 Flash takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 Flash
GLM 5.3 Flash $0.0004, GPT-5.4 Nano $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3 Flash
GLM 5.3 Flash $0.02, GPT-5.4 Nano $0.14.
Published attempt cost and pass rate

At a glance

Coding index: GLM 5.3 Flash 57.7 from 6 benchmarks, GPT-5.4 Nano 44.8 from 2 benchmarks.
Widest category: Agentic work, 26.2 points apart on average over 5 shared benchmarks.
Widest single gap: ARC-AGI-2: GLM 5.3 Flash 65.8% against GPT-5.4 Nano 5.7%, 60.1 points apart on a 0 to 100 scale.
Output price: GLM 5.3 Flash $0.50 against GPT-5.4 Nano $1.25 per million output tokens, 2.5x apart.
Context window: GLM 5.3 Flash 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
Category	GLM 5.3 Flash	GPT-5.4 Nano
Coding	8	2
Intelligence	2	0
Agentic work	5	0
Reasoning	12	2
Math	6	0
Knowledge	7	0
General	25	0
All shared boards	65	4

CodingLike-for-likeSix of these boards feed the Vibe Coding Index82

Coding benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	Leader
LiveBench coding	80.6%	Not measured	Only GLM 5.3 Flash measured
LMArena WebDev	1607	Not measured	Only GLM 5.3 Flash measured
AA Coding Index	71.5	56.1	GLM 5.3 Flash
LiveCodeBench (Vals AI)	80.5%	84.0%	GPT-5.4 Nano
SWE-bench Verified (Vals AI)	92.0%	69.8%	GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)	37.4%	Not measured	Only GLM 5.3 Flash measured
Vibe Code Bench (Vals AI)	30.8%	26.1%	GLM 5.3 Flash
Code migration (Vals AI)	20.5%	14.5%	GLM 5.3 Flash
ProgramBench (Vals AI)	0.0%	Not measured	Only GLM 5.3 Flash measured
IOI (Vals AI)	52.5%	Not measured	Only GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)	62.9%	41.6%	GLM 5.3 Flash
Vibe Code Bench 1-100 (Vals AI)	16.0%	Not measured	Only GLM 5.3 Flash measured
SkillsBench (Vals AI)	40.2%	Not measured	Only GLM 5.3 Flash measured
CyberBench (Vals AI)	67.9%	Not measured	Only GLM 5.3 Flash measured
SciCode	51.6%	47.2%	GLM 5.3 Flash
Terminal-Bench Hard (Artificial Analysis run)	Not measured	42.4%	Only GPT-5.4 Nano measured
FrontierCode	31.8%	Not measured	Only GLM 5.3 Flash measured
FrontierSWE	18.1%	Not measured	Only GLM 5.3 Flash measured
WeirdML	Not measured	49.2%	Only GPT-5.4 Nano measured
ALE-Bench	303.6	1004.5	GPT-5.4 Nano
LMArena Text: coding	1507	1404	GLM 5.3 Flash
LMArena Text: software and IT	1500	1402	GLM 5.3 Flash
LMArena WebDev: React	1624	Not measured	Only GLM 5.3 Flash measured
LMArena WebDev: HTML	1577	Not measured	Only GLM 5.3 Flash measured
LMArena WebDev: from an image	1578	Not measured	Only GLM 5.3 Flash measured
Neither model has a result on the other 14 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20

Intelligence benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	Leader
AA Intelligence Index	41.8	20.7	GLM 5.3 Flash
Epoch Capabilities Index	153.1	146.0	GLM 5.3 Flash

Agentic workLike-for-likePublic boards, shown as published, kept out of the index50

Agentic work benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	Leader
AA Agentic Index	50.9	16.0	GLM 5.3 Flash
LiveBench research	70.1%	Not measured	Only GLM 5.3 Flash measured
LiveBench browser	84.0%	Not measured	Only GLM 5.3 Flash measured
LiveBench long agentic	28.4%	Not measured	Only GLM 5.3 Flash measured
SREBench (Vals AI)	0.8%	Not measured	Only GLM 5.3 Flash measured
Finance Agent (Vals AI)	57.9%	38.2%	GLM 5.3 Flash
Tax Agent Bench (Vals AI)	31.6%	5.0%	GLM 5.3 Flash
Legal Research Bench (Vals AI)	45.2%	6.3%	GLM 5.3 Flash
Harvey's Legal Agent Benchmark (Vals AI)	10.4%	Not measured	Only GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)	55.9%	44.8%	GLM 5.3 Flash
Terminal-Bench-Science (Vals AI)	2.9%	Not measured	Only GLM 5.3 Flash measured
τ²-Bench Telecom	Not measured	76.0%	Only GPT-5.4 Nano measured
APEX-Agents	52.8%	Not measured	Only GLM 5.3 Flash measured
Neither model has a result on the other 28 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index122

Reasoning benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	Leader
GPQA Diamond	86.4%	77.5%	GLM 5.3 Flash
LiveBench reasoning	77.6%	Not measured	Only GLM 5.3 Flash measured
MMMU Pro (Vals AI)	86.0%	73.6%	GLM 5.3 Flash
GPQA Diamond (Artificial Analysis run)	91.2%	81.7%	GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)	39.9%	28.3%	GLM 5.3 Flash
GPQA Diamond (Epoch AI run)	90.2%	78.5%	GLM 5.3 Flash
ARC-AGI	91.0%	51.5%	GLM 5.3 Flash
ARC-AGI-2	65.8%	5.7%	GLM 5.3 Flash
Chess puzzles	21.0%	45.0%	GPT-5.4 Nano
Mystery game puzzles	8.0%	9.0%	GPT-5.4 Nano
LMArena Text: hard prompts	1490	1381	GLM 5.3 Flash
LMArena Text: expert	1511	1396	GLM 5.3 Flash
LMArena Text: hard prompts in English	1488	1387	GLM 5.3 Flash
LMArena Vision: diagrams	1317	1210	GLM 5.3 Flash
LMArena Vision: homework	1318	1225	GLM 5.3 Flash
Kagi LLM Benchmark	Not measured	39.7%	Only GPT-5.4 Nano measured
Neither model has a result on the other 6 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index60

Math benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	Leader
AIME	Not measured	88.8%	Only GPT-5.4 Nano measured
OTIS Mock AIME	93.9%	87.8%	GLM 5.3 Flash
FrontierMath, tiers 1 to 3	55.8%	44.9%	GLM 5.3 Flash
FrontierMath, tier 4	17.1%	12.2%	GLM 5.3 Flash
ProofBench	21.0%	5.0%	GLM 5.3 Flash
LMArena Text: math	1503	1405	GLM 5.3 Flash
LMArena Text: mathematical work	1497	1409	GLM 5.3 Flash
Neither model has a result on the other 6 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index70

Knowledge benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	Leader
MMLU Pro	86.1%	77.2%	GLM 5.3 Flash
LegalBench (Vals AI)	83.9%	77.9%	GLM 5.3 Flash
CaseLaw (Vals AI)	Not measured	51.9%	Only GPT-5.4 Nano measured
CorpFin (Vals AI)	Not measured	61.2%	Only GPT-5.4 Nano measured
TaxEval (Vals AI)	75.6%	67.4%	GLM 5.3 Flash
MortgageTax (Vals AI)	Not measured	59.1%	Only GPT-5.4 Nano measured
MedCode (Vals AI)	Not measured	41.0%	Only GPT-5.4 Nano measured
SimpleQA Verified	Not measured	11.7%	Only GPT-5.4 Nano measured
LMArena Text: science	1484	1374	GLM 5.3 Flash
LMArena Text: medicine and healthcare	1475	1369	GLM 5.3 Flash
LMArena Text: legal and government	1473	1368	GLM 5.3 Flash
LMArena Text: business and finance	1460	1366	GLM 5.3 Flash
Neither model has a result on the other 6 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared

Web design benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	Leader
Design Arena: websites	1272	Not measured	Only GLM 5.3 Flash measured
Design Arena: UI components	1316	Not measured	Only GLM 5.3 Flash measured
Design Arena: game dev	1278	Not measured	Only GLM 5.3 Flash measured
Design Arena: data viz	1262	Not measured	Only GLM 5.3 Flash measured
Design Arena: 3D	1316	Not measured	Only GLM 5.3 Flash measured
Design Arena: all code categories	1282	Not measured	Only GLM 5.3 Flash measured
Design Arena: SVG	1285	Not measured	Only GLM 5.3 Flash measured
Design Arena: ASCII art	1267	Not measured	Only GLM 5.3 Flash measured
LiveBench design	77.2%	Not measured	Only GLM 5.3 Flash measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index250

General benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	Leader
Vals Index	50.9%	Not measured	Only GLM 5.3 Flash measured
LiveBench data analysis	76.4%	Not measured	Only GLM 5.3 Flash measured
SAGE (Vals AI)	Not measured	38.1%	Only GPT-5.4 Nano measured
MedScribe (Vals AI)	88.9%	77.1%	GLM 5.3 Flash
Vals Multimodal Index	Not measured	47.6%	Only GPT-5.4 Nano measured
IFBench	Not measured	75.9%	Only GPT-5.4 Nano measured
Long context reasoning (AA-LCR)	80.0%	76.7%	GLM 5.3 Flash
DTBench	Not measured	80.3%	Only GPT-5.4 Nano measured
LMCA	Not measured	36.9%	Only GPT-5.4 Nano measured
Surface Evolver Bench	52.5%	Not measured	Only GLM 5.3 Flash measured
LMArena Text	1471	1372	GLM 5.3 Flash
LMArena Text: instruction following	1478	1362	GLM 5.3 Flash
LMArena Text: creative writing	1441	1315	GLM 5.3 Flash
LMArena Vision	1294	1196	GLM 5.3 Flash
LMArena Text: English	1474	1381	GLM 5.3 Flash
LMArena Text: non-English	1462	1359	GLM 5.3 Flash
LMArena Text: Chinese	1531	1391	GLM 5.3 Flash
LMArena Text: German	1462	1368	GLM 5.3 Flash
LMArena Text: Japanese	1444	1343	GLM 5.3 Flash
LMArena Text: Korean	1436	1321	GLM 5.3 Flash
LMArena Text: French	1491	1395	GLM 5.3 Flash
LMArena Text: Spanish	1475	1371	GLM 5.3 Flash
LMArena Text: Russian	1465	1363	GLM 5.3 Flash
LMArena Text: Polish	1450	1366	GLM 5.3 Flash
LMArena Text: multi-turn	1469	1382	GLM 5.3 Flash
LMArena Text: longer queries	1481	1365	GLM 5.3 Flash
LMArena Text: writing and language	1455	1338	GLM 5.3 Flash
LMArena Text: entertainment and media	1440	1325	GLM 5.3 Flash
LMArena Vision: English	1295	1202	GLM 5.3 Flash
LMArena Vision: Chinese	1363	1232	GLM 5.3 Flash
LMArena Vision: reading text	1299	1204	GLM 5.3 Flash
LMArena Vision: humor	1279	1161	GLM 5.3 Flash
LMArena Vision: recognizing things	Not measured	1141	Only GPT-5.4 Nano measured
LMArena Vision: creative writing	1270	1159	GLM 5.3 Flash
Neither model has a result on the other 12 boards here

Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Image generation benchmarks for GLM 5.3 Flash and GPT-5.4 Nano
Benchmark	GLM 5.3 Flash	GPT-5.4 Nano	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 5.3 Flash$0.0004Fits in one request

GPT-5.4 Nano$0.0008Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Flash$0.0090Fits in one request

GPT-5.4 Nano$0.014Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Flash$0.035Fits in one request

GPT-5.4 Nano$0.052Fits in one request

GLM 5.3 Flash 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 5.3 Flash and GPT-5.4 Nano
Specification	Z.ai GLM 5.3 Flash	OpenAI GPT-5.4 Nano
Maker	Z.ai	OpenAI
Weights	Open weights	No public weights listed
Released	August 26, 2026	March 17, 2026
Context window	1.05M	400K
Input $/Mtok	$0.15	$0.20
Output $/Mtok	$0.50	$1.25
Coding index	57.7	44.8
Independent measurements behind it	6	2
Cost per solved task	$0.02	$0.14
Source	OpenRouter listing	OpenRouter listing

Questions

Is GLM 5.3 Flash better than GPT-5.4 Nano for coding?

Pick GLM 5.3 Flash for coding: it scores 57.7 on the Vibe Coding Index against 44.8 for GPT-5.4 Nano. Pick GPT-5.4 Nano for work measured by LiveCodeBench (Vals AI) or ALE-Bench, where it leads.

Which is cheaper, GLM 5.3 Flash or GPT-5.4 Nano?

GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; GPT-5.4 Nano costs $0.20 and $1.25. Per solved SWE-bench Verified task, GLM 5.3 Flash costs $0.02 and GPT-5.4 Nano $0.14.

Which has the bigger context window, GLM 5.3 Flash or GPT-5.4 Nano?

GLM 5.3 Flash, with 1.05M tokens against 400K.

How many benchmarks is the GLM 5.3 Flash vs GPT-5.4 Nano comparison based on?

69 benchmarks have a result for both models as of October 22, 2026. GLM 5.3 Flash's coding index rests on 6 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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GLM 5.3 Flash or GPT-5.4 Nano: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

General

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next