GLM 4.6 vs GPT-5.6 Luna

GPT-5.6 Luna leads GLM 4.6 on coding, 58.0 to 8.8 on the Vibe Coding Index, and GPT-5.6 Luna costs 1.8x less per output token ($1.20 vs $2.20 per million). Updated October 22, 2026; 50 benchmarks have a result for both.

Replace GLM 4.6 Replace GPT-5.6 Luna

GLM 4.6Z.ai

Coding: 8.8
Overall: 33.4
Output $/M: $2.20

GPT-5.6 LunaOpenAI

Coding: 58.0
Overall: 61.6
Output $/M: $1.20

vs boards won of 50 shared

GLM 4.6 or GPT-5.6 Luna: which to pick

Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.

Model AGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task Model BGPT-5.6 LunaOpenAI58.0/1006 independent benchmarks$0.04 per solved task

501969

Shared results: 50
GLM 4.6 only: 19
GPT-5.6 Luna only: 69
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
GPT-5.6 Luna
GPT-5.6 Luna scores 58.0 against 8.8.
2 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 37.3 against 18.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Luna has a AA Agentic Index result, 42.1.
Directional only
Reasoning
GPQA Diamond
GPT-5.6 Luna
GPT-5.6 Luna leads, 91.7% against 74.5%.
Same board, both measured
Math
AIME
No call
Only GLM 4.6 has a AIME result, 92.7%.
Directional only
Knowledge
MMLU Pro
GPT-5.6 Luna
GPT-5.6 Luna leads, 86.0% against 82.2%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.6 Luna
GPT-5.6 Luna leads, 1255 against 1174.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Luna
GPT-5.6 Luna takes 1.05M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.6 Luna
GLM 4.6 $0.0017, GPT-5.6 Luna $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Luna has the number, $0.04.
Directional only

At a glance

Coding index: GLM 4.6 8.8 from 2 benchmarks, GPT-5.6 Luna 58.0 from 6 benchmarks.
Widest category: Coding, 28.8 points apart on average over 7 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): GLM 4.6 3.1% against GPT-5.6 Luna 77.1%, 74.0 points apart on a 0 to 100 scale.
Output price: GLM 4.6 $2.20 against GPT-5.6 Luna $1.20 per million output tokens, 1.8x apart.
Context window: GLM 4.6 takes 205K 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 4.6	GPT-5.6 Luna
Coding	0	7
Intelligence	0	1
Reasoning	0	7
Math	0	2
Knowledge	3	5
Web design	1	6
General	8	10
All shared boards	12	38

CodingLike-for-likeSix of these boards feed the Vibe Coding Index07

Coding benchmarks for GLM 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	GPT-5.6 Luna	Leader
SWE-bench Verified	68.2%	Not measured	Only GLM 4.6 measured
LiveBench coding	Not measured	73.6%	Only GPT-5.6 Luna measured
LMArena WebDev	1341	1518	GPT-5.6 Luna
AA Coding Index	45.8	71.4	GPT-5.6 Luna
LiveCodeBench (Vals AI)	81.0%	Not measured	Only GLM 4.6 measured
SWE-bench Verified (Vals AI)	Not measured	93.0%	Only GPT-5.6 Luna measured
Terminal-Bench 4 (Vals AI)	Not measured	11.6%	Only GPT-5.6 Luna measured
Vibe Code Bench (Vals AI)	3.1%	77.1%	GPT-5.6 Luna
Code migration (Vals AI)	Not measured	44.5%	Only GPT-5.6 Luna measured
ProgramBench (Vals AI)	Not measured	0.0%	Only GPT-5.6 Luna measured
IOI (Vals AI)	Not measured	61.8%	Only GPT-5.6 Luna measured
Terminal-Bench 2.1 (Vals AI)	Not measured	79.0%	Only GPT-5.6 Luna measured
Vibe Code Bench 1-100 (Vals AI)	Not measured	22.6%	Only GPT-5.6 Luna measured
SkillsBench (Vals AI)	Not measured	60.5%	Only GPT-5.6 Luna measured
CyberBench (Vals AI)	Not measured	73.6%	Only GPT-5.6 Luna measured
LiveCodeBench (Artificial Analysis run)	69.5%	Not measured	Only GLM 4.6 measured
SciCode	Not measured	53.6%	Only GPT-5.6 Luna measured
Terminal-Bench Hard (Artificial Analysis run)	28.8%	Not measured	Only GLM 4.6 measured
Terminal-Bench	24.5%	Not measured	Only GLM 4.6 measured
FrontierCode	Not measured	39.8%	Only GPT-5.6 Luna measured
WeirdML	Not measured	60.9%	Only GPT-5.6 Luna measured
ALE-Bench	340.8	1667.4	GPT-5.6 Luna
LMArena Text: coding	1449	1466	GPT-5.6 Luna
LMArena Text: software and IT	1455	1463	GPT-5.6 Luna
LMArena WebDev: React	Not measured	1508	Only GPT-5.6 Luna measured
LMArena WebDev: HTML	1350	1520	GPT-5.6 Luna
LMArena WebDev: from an image	Not measured	1517	Only GPT-5.6 Luna measured
SciCode	Not measured	6.2%	Only GPT-5.6 Luna measured
Neither model has a result on the other 11 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01

Intelligence benchmarks for GLM 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	GPT-5.6 Luna	Leader
AA Intelligence Index	18.5	37.3	GPT-5.6 Luna
Epoch Capabilities Index	Not measured	156.5	Only GPT-5.6 Luna measured

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index22 boards, none shared

Agentic work benchmarks for GLM 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	GPT-5.6 Luna	Leader
AA Agentic Index	Not measured	42.1	Only GPT-5.6 Luna measured
Design Arena: agents building full-stack apps	1029	Not measured	Only GLM 4.6 measured
Design Arena: agents building mobile apps	1096	Not measured	Only GLM 4.6 measured
Design Arena: agents building Android apps	1084	Not measured	Only GLM 4.6 measured
Design Arena: agents building Godot games	1180	Not measured	Only GLM 4.6 measured
LiveBench research	Not measured	51.0%	Only GPT-5.6 Luna measured
LiveBench browser	Not measured	68.0%	Only GPT-5.6 Luna measured
LiveBench long agentic	Not measured	30.4%	Only GPT-5.6 Luna measured
SREBench (Vals AI)	Not measured	1.5%	Only GPT-5.6 Luna measured
Finance Agent (Vals AI)	Not measured	55.0%	Only GPT-5.6 Luna measured
Tax Agent Bench (Vals AI)	Not measured	24.8%	Only GPT-5.6 Luna measured
Legal Research Bench (Vals AI)	Not measured	36.5%	Only GPT-5.6 Luna measured
Excel Modeling Benchmark (Vals AI)	Not measured	67.1%	Only GPT-5.6 Luna measured
BioMysteryBench (Vals AI)	Not measured	61.5%	Only GPT-5.6 Luna measured
Terminal-Bench-Science (Vals AI)	Not measured	0.0%	Only GPT-5.6 Luna measured
Vals Science Index	Not measured	25.3%	Only GPT-5.6 Luna measured
τ²-Bench Telecom	76.9%	Not measured	Only GLM 4.6 measured
APEX-Agents	Not measured	43.0%	Only GPT-5.6 Luna measured
BALROG	Not measured	45.6%	Only GPT-5.6 Luna measured
Vending-Bench 2	Not measured	$4,095	Only GPT-5.6 Luna measured
Berkeley Function Calling Leaderboard (BFCL)	72.4%	Not measured	Only GLM 4.6 measured
BrowseComp-Plus	48.2%	Not measured	Only GLM 4.6 measured
Neither model has a result on the other 19 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index07

Reasoning benchmarks for GLM 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	GPT-5.6 Luna	Leader
GPQA Diamond	74.5%	91.7%	GPT-5.6 Luna
LiveBench reasoning	Not measured	85.6%	Only GPT-5.6 Luna measured
MysteryMechanism (Vals AI)	Not measured	14.4%	Only GPT-5.6 Luna measured
MMMU Pro (Vals AI)	Not measured	85.0%	Only GPT-5.6 Luna measured
GPQA Diamond (Artificial Analysis run)	78.0%	91.1%	GPT-5.6 Luna
Humanity's Last Exam (Artificial Analysis run)	14.5%	39.5%	GPT-5.6 Luna
GPQA Diamond (Epoch AI run)	Not measured	91.6%	Only GPT-5.6 Luna measured
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	Not measured	43.0%	Only GPT-5.6 Luna measured
Mystery game puzzles	Not measured	21.0%	Only GPT-5.6 Luna measured
LMArena Text: hard prompts	1440	1451	GPT-5.6 Luna
LMArena Text: expert	1432	1478	GPT-5.6 Luna
LMArena Text: hard prompts in English	1445	1460	GPT-5.6 Luna
LMArena Vision: diagrams	Not measured	1273	Only GPT-5.6 Luna measured
LMArena Vision: homework	Not measured	1282	Only GPT-5.6 Luna measured
Kagi LLM Benchmark	45.7%	49.1%	GPT-5.6 Luna
Neither model has a result on the other 4 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index02

Math benchmarks for GLM 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	GPT-5.6 Luna	Leader
AIME	92.7%	Not measured	Only GLM 4.6 measured
MGSM (Vals AI)	89.8%	Not measured	Only GLM 4.6 measured
AA Math Index	86.0	Not measured	Only GLM 4.6 measured
AIME 2025 (Artificial Analysis run)	86.0%	Not measured	Only GLM 4.6 measured
OTIS Mock AIME	Not measured	98.3%	Only GPT-5.6 Luna measured
FrontierMath, tiers 1 to 3	Not measured	82.1%	Only GPT-5.6 Luna measured
FrontierMath, tier 4	Not measured	61.0%	Only GPT-5.6 Luna measured
ProofBench	Not measured	60.0%	Only GPT-5.6 Luna measured
LMArena Text: math	1432	1459	GPT-5.6 Luna
LMArena Text: mathematical work	1447	1470	GPT-5.6 Luna
Neither model has a result on the other 3 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index35

Knowledge benchmarks for GLM 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	GPT-5.6 Luna	Leader
MMLU Pro	82.2%	86.0%	GPT-5.6 Luna
LegalBench (Vals AI)	79.6%	84.0%	GPT-5.6 Luna
CorpFin (Vals AI)	56.8%	64.2%	GPT-5.6 Luna
TaxEval (Vals AI)	66.2%	76.2%	GPT-5.6 Luna
MortgageTax (Vals AI)	Not measured	67.3%	Only GPT-5.6 Luna measured
MedQA (Vals AI)	92.2%	Not measured	Only GLM 4.6 measured
MedCode (Vals AI)	Not measured	42.4%	Only GPT-5.6 Luna measured
MMLU Pro (Artificial Analysis run)	82.9%	Not measured	Only GLM 4.6 measured
SimpleQA Verified	Not measured	41.0%	Only GPT-5.6 Luna measured
LMArena Text: science	1456	1433	GLM 4.6
LMArena Text: medicine and healthcare	1455	1399	GLM 4.6
LMArena Text: legal and government	1448	1446	GLM 4.6
LMArena Text: business and finance	1416	1439	GPT-5.6 Luna
FACTS Benchmark Suite	Not measured	35.0%	Only GPT-5.6 Luna measured
Neither model has a result on the other 4 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index16

Web design benchmarks for GLM 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	GPT-5.6 Luna	Leader
Design Arena: websites	1174	1255	GPT-5.6 Luna
Design Arena: UI components	1145	1248	GPT-5.6 Luna
Design Arena: game dev	1150	1194	GPT-5.6 Luna
Design Arena: data viz	1161	1211	GPT-5.6 Luna
Design Arena: 3D	1128	1121	GLM 4.6
Design Arena: all code categories	1165	1231	GPT-5.6 Luna
Design Arena: SVG	1108	1194	GPT-5.6 Luna
Design Arena: ASCII art	Not measured	1142	Only GPT-5.6 Luna measured
LiveBench design	Not measured	76.0%	Only GPT-5.6 Luna measured

GeneralLike-for-likePublic boards, shown as published, kept out of the index810

General benchmarks for GLM 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	GPT-5.6 Luna	Leader
LiveBench data analysis	Not measured	78.0%	Only GPT-5.6 Luna measured
Public Benefits Bench (Vals AI)	Not measured	61.2%	Only GPT-5.6 Luna measured
SAGE (Vals AI)	Not measured	44.2%	Only GPT-5.6 Luna measured
MedScribe (Vals AI)	Not measured	84.4%	Only GPT-5.6 Luna measured
Vals Multimodal Index	Not measured	69.1%	Only GPT-5.6 Luna measured
IFBench	43.4%	Not measured	Only GLM 4.6 measured
Long context reasoning (AA-LCR)	54.0%	83.7%	GPT-5.6 Luna
DTBench	Not measured	89.1%	Only GPT-5.6 Luna measured
LMCA	Not measured	48.5%	Only GPT-5.6 Luna measured
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	1440	1431	GLM 4.6
LMArena Text: instruction following	1410	1437	GPT-5.6 Luna
LMArena Text: creative writing	1412	1396	GLM 4.6
LMArena Vision	Not measured	1257	Only GPT-5.6 Luna measured
LMArena Text: English	1449	1441	GLM 4.6
LMArena Text: non-English	1426	1417	GLM 4.6
LMArena Text: Chinese	1499	1470	GLM 4.6
LMArena Text: German	1447	1455	GPT-5.6 Luna
LMArena Text: Japanese	1393	1415	GPT-5.6 Luna
LMArena Text: Korean	1400	1415	GPT-5.6 Luna
LMArena Text: French	1459	1458	GLM 4.6
LMArena Text: Spanish	1436	1446	GPT-5.6 Luna
LMArena Text: Russian	1418	1427	GPT-5.6 Luna
LMArena Text: Polish	1447	1405	GLM 4.6
LMArena Text: multi-turn	1427	1434	GPT-5.6 Luna
LMArena Text: longer queries	1422	1436	GPT-5.6 Luna
LMArena Text: writing and language	1415	1419	GPT-5.6 Luna
LMArena Text: entertainment and media	1409	1402	GLM 4.6
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 4.6 and GPT-5.6 Luna
Benchmark	GLM 4.6	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 4.6$0.0017Fits in one request

GPT-5.6 Luna$0.0008Fits in one request

GPT-5.6 Luna costs less

Repository review

50K input + 3K output tokens

GLM 4.6$0.037Fits in one request

GPT-5.6 Luna$0.014Fits in one request

GPT-5.6 Luna costs less

Agent loop

200K input + 10K output tokens

GLM 4.6$0.142Exceeds the context window

GPT-5.6 Luna$0.052Fits in one request

GPT-5.6 Luna 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 4.6 and GPT-5.6 Luna
Specification	Z.ai GLM 4.6	OpenAI GPT-5.6 Luna
Maker	Z.ai	OpenAI
Weights	Open weights	No public weights listed
Released	September 30, 2025	July 9, 2026
Context window	205K	1.05M
Input $/Mtok	$0.60	$0.20
Output $/Mtok	$2.20	$1.20
Coding index	8.8	58.0
Independent measurements behind it	2	6
Cost per solved task	Not computable	$0.04
Source	OpenRouter listing	OpenRouter listing

Questions

Is GLM 4.6 better than GPT-5.6 Luna for coding?

Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.

Which is cheaper, GLM 4.6 or GPT-5.6 Luna?

GLM 4.6 costs $0.60 per million input tokens and $2.20 per million output tokens; GPT-5.6 Luna costs $0.20 and $1.20. Cost per solved task is known for GPT-5.6 Luna only.

Which has the bigger context window, GLM 4.6 or GPT-5.6 Luna?

GPT-5.6 Luna, with 1.05M tokens against 205K.

How many benchmarks is the GLM 4.6 vs GPT-5.6 Luna comparison based on?

50 benchmarks have a result for both models as of October 22, 2026. GLM 4.6's coding index rests on 2 independent benchmarks and GPT-5.6 Luna's on 6. Where only one model has a result, the page says so instead of naming a winner.

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GLM 4.6 or GPT-5.6 Luna: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

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