GLM 5.3 vs GPT-5.6 Luna

Updated October 21, 2026. 93 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 5.3 Replace GPT-5.6 Luna

GLM 5.3Z.ai

Coding: 73.1
Overall: 44.8
Output $/M: $1.40

GPT-5.6 LunaOpenAI

Coding: 61.5
Overall: 37.3
Output $/M: $1.20

vs boards won of 93 shared, 1 tied

Decision reading

Pick GLM 5.3 for coding: it scores 73.1 on the Vibe Coding Index against 61.5 for GPT-5.6 Luna.

Pick GPT-5.6 Luna when output tokens cost 1.2x less, or when a solved task costs $0.04 against $0.36.

Model AGLM 5.3Z.ai73.1/1002 independent benchmarks$0.36 per solved task Model BGPT-5.6 LunaOpenAI61.5/1002 independent benchmarks$0.04 per solved task

93723

Shared results: 93
GLM 5.3 only: 7
GPT-5.6 Luna only: 23
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.

Coding
Vibe Coding Index, four public coding benchmarks
GLM 5.3
GLM 5.3 scores 73.1 against 61.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GLM 5.3
GLM 5.3 leads, 44.8 against 37.3.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3
GLM 5.3 leads, 53.1 against 42.1.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Luna
GPT-5.6 Luna leads, 91.7% against 88.1%.
Same board, both measured
Knowledge
MMLU Pro
GLM 5.3
GLM 5.3 leads, 86.8% against 86.0%.
Same board, both measured
Web design
Design Arena: websites
GLM 5.3
GLM 5.3 leads, 1295 against 1256.
Same board, both measured
General
Vals Index
No call
Only GLM 5.3 has a Vals Index result, 59.7%.
Directional only
Long documents
Listed context window
GPT-5.6 Luna
GPT-5.6 Luna takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3
GLM 5.3 $0.0008, GPT-5.6 Luna $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.6 Luna
GLM 5.3 $0.36, GPT-5.6 Luna $0.04.
Published attempt cost and pass rate

At a glance

Coding index: GLM 5.3 73.1 from 2 benchmarks, GPT-5.6 Luna 61.5 from 2 benchmarks.
Widest category: Agentic work, 16.5 points apart on average over 12 shared benchmarks.
Widest single gap: LiveBench browser: GLM 5.3 0.0% against GPT-5.6 Luna 68.0%, 68.0 points apart on a 0 to 100 scale.
Output price: GLM 5.3 $1.40 against GPT-5.6 Luna $1.20 per million output tokens, 1.2x apart.
Context window: GLM 5.3 takes 1.05M tokens, GPT-5.6 Luna 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
Category	GLM 5.3	GPT-5.6 Luna	Ties
Coding	15	6
Intelligence	1	1
Agentic work	10	2
Reasoning	8	3
Math	2	4
Knowledge	7	1	1 tie
Web design	9	0
General	20	3
All shared boards	72	20	1 tie

CodingLike-for-likeFour of these boards feed the Vibe Coding Index156

Coding benchmarks for GLM 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	Leader
LiveBench coding	82.8%	73.6%	GLM 5.3
LMArena WebDev	1621	1518	GLM 5.3
AA Coding Index	74.8	71.4	GLM 5.3
LiveCodeBench (Vals AI)	80.5%	Not measured	Only GLM 5.3 measured
SWE-bench Verified (Vals AI)	95.4%	93.0%	GLM 5.3
Terminal-Bench 4 (Vals AI)	38.9%	11.6%	GLM 5.3
Vibe Code Bench (Vals AI)	78.1%	77.1%	GLM 5.3
Code migration (Vals AI)	44.2%	44.5%	GPT-5.6 Luna
ProgramBench (Vals AI)	1.5%	0.0%	GLM 5.3
IOI (Vals AI)	68.4%	61.8%	GLM 5.3
Terminal-Bench 2.1 (Vals AI)	71.5%	79.0%	GPT-5.6 Luna
Vibe Code Bench 1-100 (Vals AI)	20.0%	22.6%	GPT-5.6 Luna
SkillsBench (Vals AI)	47.5%	60.5%	GPT-5.6 Luna
CyberBench (Vals AI)	72.1%	73.6%	GPT-5.6 Luna
SciCode	59.0%	53.6%	GLM 5.3
FrontierCode	40.1%	39.8%	GLM 5.3
FrontierSWE	30.2%	Not measured	Only GLM 5.3 measured
WeirdML	75.4%	60.9%	GLM 5.3
ALE-Bench	1317.4	1667.4	GPT-5.6 Luna
LMArena Text: coding	1497	1466	GLM 5.3
LMArena Text: software and IT	1493	1463	GLM 5.3
LMArena WebDev: React	1641	1508	GLM 5.3
LMArena WebDev: HTML	1595	1520	GLM 5.3
LMArena WebDev: from an image	Not measured	1517	Only GPT-5.6 Luna measured
Neither model has a result on the other 14 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11

Intelligence benchmarks for GLM 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	Leader
AA Intelligence Index	44.8	37.3	GLM 5.3
Epoch Capabilities Index	156.0	156.5	GPT-5.6 Luna

Agentic workLike-for-likePublic boards, shown as published, kept out of the index102

Agentic work benchmarks for GLM 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	Leader
AA Agentic Index	53.1	42.1	GLM 5.3
Design Arena: agents building mobile apps	1194	Not measured	Only GLM 5.3 measured
Design Arena: HTML slides	1189	Not measured	Only GLM 5.3 measured
Design Arena: PowerPoint slides	1255	Not measured	Only GLM 5.3 measured
LiveBench research	73.2%	51.0%	GLM 5.3
LiveBench browser	0.0%	68.0%	GPT-5.6 Luna
LiveBench long agentic	35.9%	30.4%	GLM 5.3
SREBench (Vals AI)	9.2%	1.5%	GLM 5.3
Finance Agent (Vals AI)	55.8%	55.0%	GLM 5.3
Tax Agent Bench (Vals AI)	39.7%	24.8%	GLM 5.3
Legal Research Bench (Vals AI)	49.0%	36.5%	GLM 5.3
Harvey's Legal Agent Benchmark (Vals AI)	14.6%	Not measured	Only GLM 5.3 measured
Excel Modeling Benchmark (Vals AI)	56.3%	67.1%	GPT-5.6 Luna
BioMysteryBench (Vals AI)	Not measured	61.5%	Only GPT-5.6 Luna measured
Terminal-Bench-Science (Vals AI)	5.7%	0.0%	GLM 5.3
Vals Science Index	Not measured	25.3%	Only GPT-5.6 Luna measured
APEX-Agents	56.6%	43.0%	GLM 5.3
BALROG	Not measured	45.6%	Only GPT-5.6 Luna measured
Vending-Bench 2	$8,164	$4,095	GLM 5.3
Neither model has a result on the other 20 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index83

Reasoning benchmarks for GLM 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	Leader
GPQA Diamond	88.1%	91.7%	GPT-5.6 Luna
LiveBench reasoning	85.8%	85.6%	GLM 5.3
MysteryMechanism (Vals AI)	23.0%	14.4%	GLM 5.3
MMMU Pro (Vals AI)	Not measured	85.0%	Only GPT-5.6 Luna measured
GPQA Diamond (Artificial Analysis run)	91.7%	91.1%	GLM 5.3
Humanity's Last Exam (Artificial Analysis run)	42.3%	39.5%	GLM 5.3
GPQA Diamond (Epoch AI run)	90.9%	91.6%	GPT-5.6 Luna
ARC-AGI	Not measured	88.0%	Only GPT-5.6 Luna measured
ARC-AGI-2	Not measured	59.5%	Only GPT-5.6 Luna measured
SimpleBench	Not measured	46.8%	Only GPT-5.6 Luna measured
Chess puzzles	37.0%	43.0%	GPT-5.6 Luna
Mystery game puzzles	33.0%	21.0%	GLM 5.3
LMArena Text: hard prompts	1490	1451	GLM 5.3
LMArena Text: expert	1514	1478	GLM 5.3
LMArena Text: hard prompts in English	1496	1460	GLM 5.3
LMArena Vision: diagrams	Not measured	1273	Only GPT-5.6 Luna measured
LMArena Vision: homework	Not measured	1282	Only GPT-5.6 Luna measured
Neither model has a result on the other 4 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index24

Math benchmarks for GLM 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	Leader
OTIS Mock AIME	91.1%	98.3%	GPT-5.6 Luna
FrontierMath, tiers 1 to 3	68.8%	82.1%	GPT-5.6 Luna
FrontierMath, tier 4	29.3%	61.0%	GPT-5.6 Luna
ProofBench	49.0%	60.0%	GPT-5.6 Luna
LMArena Text: math	1495	1459	GLM 5.3
LMArena Text: mathematical work	1497	1470	GLM 5.3
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index71

Knowledge benchmarks for GLM 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	Leader
MMLU Pro	86.8%	86.0%	GLM 5.3
LegalBench (Vals AI)	84.8%	84.0%	GLM 5.3
CorpFin (Vals AI)	Not measured	64.2%	Only GPT-5.6 Luna measured
TaxEval (Vals AI)	72.4%	76.2%	GPT-5.6 Luna
MortgageTax (Vals AI)	Not measured	67.3%	Only GPT-5.6 Luna measured
MedCode (Vals AI)	42.9%	42.4%	GLM 5.3
SimpleQA Verified	41.0%	41.0%	Tie
LMArena Text: science	1498	1433	GLM 5.3
LMArena Text: medicine and healthcare	1481	1399	GLM 5.3
LMArena Text: legal and government	1473	1446	GLM 5.3
LMArena Text: business and finance	1459	1439	GLM 5.3
Neither model has a result on the other 6 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index90

Web design benchmarks for GLM 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	Leader
Design Arena: websites	1295	1256	GLM 5.3
Design Arena: UI components	1314	1250	GLM 5.3
Design Arena: game dev	1311	1196	GLM 5.3
Design Arena: data viz	1260	1212	GLM 5.3
Design Arena: 3D	1332	1121	GLM 5.3
Design Arena: all code categories	1304	1231	GLM 5.3
Design Arena: SVG	1292	1193	GLM 5.3
Design Arena: ASCII art	1213	1144	GLM 5.3
LiveBench design	77.3%	76.0%	GLM 5.3

GeneralLike-for-likePublic boards, shown as published, kept out of the index203

General benchmarks for GLM 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	Leader
Vals Index	59.7%	Not measured	Only GLM 5.3 measured
LiveBench data analysis	70.2%	78.0%	GPT-5.6 Luna
Public Benefits Bench (Vals AI)	68.5%	61.2%	GLM 5.3
SAGE (Vals AI)	Not measured	44.2%	Only GPT-5.6 Luna measured
MedScribe (Vals AI)	88.8%	84.4%	GLM 5.3
Vals Multimodal Index	Not measured	69.1%	Only GPT-5.6 Luna measured
Long context reasoning (AA-LCR)	79.7%	83.7%	GPT-5.6 Luna
DTBench	87.7%	89.1%	GPT-5.6 Luna
LMCA	55.5%	48.5%	GLM 5.3
Surface Evolver Bench	Not measured	61.9%	Only GPT-5.6 Luna measured
Furniture assembly	Not measured	42.5%	Only GPT-5.6 Luna measured
LMArena Text	1474	1431	GLM 5.3
LMArena Text: instruction following	1479	1437	GLM 5.3
LMArena Text: creative writing	1458	1396	GLM 5.3
LMArena Vision	Not measured	1257	Only GPT-5.6 Luna measured
LMArena Text: English	1482	1441	GLM 5.3
LMArena Text: non-English	1459	1417	GLM 5.3
LMArena Text: Chinese	1532	1470	GLM 5.3
LMArena Text: German	1488	1455	GLM 5.3
LMArena Text: Japanese	1460	1415	GLM 5.3
LMArena Text: Korean	1460	1415	GLM 5.3
LMArena Text: French	1503	1458	GLM 5.3
LMArena Text: Spanish	1462	1446	GLM 5.3
LMArena Text: Russian	1469	1427	GLM 5.3
LMArena Text: Polish	1466	1405	GLM 5.3
LMArena Text: multi-turn	1472	1434	GLM 5.3
LMArena Text: longer queries	1483	1436	GLM 5.3
LMArena Text: writing and language	1469	1419	GLM 5.3
LMArena Text: entertainment and media	1447	1402	GLM 5.3
LMArena Vision: English	Not measured	1263	Only GPT-5.6 Luna measured
LMArena Vision: Chinese	Not measured	1294	Only GPT-5.6 Luna measured
LMArena Vision: reading text	Not measured	1264	Only GPT-5.6 Luna measured
LMArena Vision: humor	Not measured	1190	Only GPT-5.6 Luna measured
LMArena Vision: creative writing	Not measured	1257	Only GPT-5.6 Luna measured
LMArena Document	Not measured	1457	Only GPT-5.6 Luna 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 5.3 and GPT-5.6 Luna
Benchmark	GLM 5.3	GPT-5.6 Luna	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$0.0008Fits in one request

GPT-5.6 Luna$0.0008Fits in one request

GLM 5.3 costs less

Repository review

50K input + 3K output tokens

GLM 5.3$0.0081Fits in one request

GPT-5.6 Luna$0.014Fits in one request

GLM 5.3 costs less

Agent loop

200K input + 10K output tokens

GLM 5.3$0.030Fits in one request

GPT-5.6 Luna$0.052Fits in one request

GLM 5.3 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 and GPT-5.6 Luna
Specification	Z.ai GLM 5.3	OpenAI GPT-5.6 Luna
Maker	Z.ai	OpenAI
Weights	Open weights	No public weights listed
Released	August 18, 2026	July 9, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.079	$0.20
Output $/Mtok	$1.40	$1.20
Coding index	73.1	61.5
Independent measurements behind it	2	2
Cost per solved task	$0.36	$0.04
Source	OpenRouter listing	OpenRouter listing

Questions

Is GLM 5.3 better than GPT-5.6 Luna for coding?

Pick GLM 5.3 for coding: it scores 73.1 on the Vibe Coding Index against 61.5 for GPT-5.6 Luna. Pick GPT-5.6 Luna when output tokens cost 1.2x less, or when a solved task costs $0.04 against $0.36.

Which is cheaper, GLM 5.3 or GPT-5.6 Luna?

GLM 5.3 costs $0.079 per million input tokens and $1.40 per million output tokens; GPT-5.6 Luna costs $0.20 and $1.20. Per solved SWE-bench Verified task, GLM 5.3 costs $0.36 and GPT-5.6 Luna $0.04.

Which has the bigger context window, GLM 5.3 or GPT-5.6 Luna?

GPT-5.6 Luna, with 1.05M tokens against 1.05M.

How many benchmarks is the GLM 5.3 vs GPT-5.6 Luna comparison based on?

93 benchmarks have a result for both models as of October 21, 2026. GLM 5.3's coding index rests on 2 independent benchmarks and GPT-5.6 Luna's on 2. Where only one model has a result, the page says so instead of naming a winner.

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Decision reading

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

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