GLM 5.3 vs Grok 4.6

GLM 5.3 leads Grok 4.6 on coding, 70.6 to 65.7 on the Vibe Coding Index, and GLM 5.3 costs 1.4x less per output token ($4.40 vs $6.00 per million). Updated October 21, 2026; 97 benchmarks have a result for both.

Replace GLM 5.3 Replace Grok 4.6

GLM 5.3Z.ai

Coding: 70.6
Overall: 67.9
Output $/M: $4.40

Grok 4.6xAI

Coding: 65.7
Overall: 67.4
Output $/M: $6.00

vs boards won of 97 shared

GLM 5.3 or Grok 4.6: which to pick

Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 65.7 for Grok 4.6.

Pick Grok 4.6 for work measured by LiveBench coding or AA Coding Index, where it leads.

Model AGLM 5.3Z.ai70.6/1006 independent benchmarks$0.36 per solved task Model BGrok 4.6xAI65.7/1006 independent benchmarks$0.82 per solved task

97326

Shared results: 97
GLM 5.3 only: 3
Grok 4.6 only: 26
Like-for-like categories: 8 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
GLM 5.3 scores 70.6 against 65.7.
6 benchmarks behind each score
Intelligence
AA Intelligence Index
GLM 5.3
GLM 5.3 leads, 44.8 against 44.3.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3
GLM 5.3 leads, 53.1 against 53.0.
Same board, both measured
Reasoning
GPQA Diamond
Grok 4.6
Grok 4.6 leads, 94.7% against 88.1%.
Same board, both measured
Knowledge
MMLU Pro
Grok 4.6
Grok 4.6 leads, 89.4% against 86.8%.
Same board, both measured
Web design
Design Arena: websites
GLM 5.3
GLM 5.3 leads, 1295 against 1289.
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
GLM 5.3
GLM 5.3 takes 1.05M tokens against 500K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3
GLM 5.3 $0.0036, Grok 4.6 $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3
GLM 5.3 $0.36, Grok 4.6 $0.82.
Published attempt cost and pass rate

At a glance

Coding index: GLM 5.3 70.6 from 6 benchmarks, Grok 4.6 65.7 from 6 benchmarks.
Widest category: Agentic work, 9.3 points apart on average over 14 shared benchmarks.
Widest single gap: LiveBench browser: GLM 5.3 0.0% against Grok 4.6 64.0%, 64.0 points apart on a 0 to 100 scale.
Output price: GLM 5.3 $4.40 against Grok 4.6 $6.00 per million output tokens, 1.4x apart.
Context window: GLM 5.3 takes 1.05M tokens, Grok 4.6 500K.

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	Grok 4.6
Coding	13	10
Intelligence	1	1
Agentic work	5	9
Reasoning	4	7
Math	3	3
Knowledge	5	4
Web design	6	3
General	20	3
All shared boards	57	40

CodingLike-for-likeSix of these boards feed the Vibe Coding Index1310

Coding benchmarks for GLM 5.3 and Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	Leader
LiveBench coding	82.8%	89.1%	Grok 4.6
LMArena WebDev	1621	1617	GLM 5.3
AA Coding Index	74.8	76.8	Grok 4.6
LiveCodeBench (Vals AI)	80.5%	88.2%	Grok 4.6
SWE-bench Verified (Vals AI)	95.4%	95.6%	Grok 4.6
Terminal-Bench 4 (Vals AI)	38.9%	17.2%	GLM 5.3
Vibe Code Bench (Vals AI)	78.1%	76.2%	GLM 5.3
Code migration (Vals AI)	44.2%	44.6%	Grok 4.6
ProgramBench (Vals AI)	1.5%	1.0%	GLM 5.3
IOI (Vals AI)	68.4%	47.6%	GLM 5.3
Terminal-Bench 2.1 (Vals AI)	71.5%	78.3%	Grok 4.6
Vibe Code Bench 1-100 (Vals AI)	20.0%	14.8%	GLM 5.3
SkillsBench (Vals AI)	47.5%	55.8%	Grok 4.6
CyberBench (Vals AI)	72.1%	67.7%	GLM 5.3
SciCode	59.0%	56.5%	GLM 5.3
FrontierCode	40.1%	48.0%	Grok 4.6
FrontierSWE	30.2%	25.3%	GLM 5.3
WeirdML	75.4%	67.3%	GLM 5.3
ALE-Bench	1317.4	1508.1	Grok 4.6
LMArena Text: coding	1497	1466	GLM 5.3
LMArena Text: software and IT	1493	1457	GLM 5.3
LMArena WebDev: React	1641	1631	GLM 5.3
LMArena WebDev: HTML	1595	1597	Grok 4.6
LMArena WebDev: from an image	Not measured	1603	Only Grok 4.6 measured
Neither model has a result on the other 15 boards here

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

Intelligence benchmarks for GLM 5.3 and Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	Leader
AA Intelligence Index	44.8	44.3	GLM 5.3
Epoch Capabilities Index	156.0	156.6	Grok 4.6

Agentic workLike-for-likePublic boards, shown as published, kept out of the index59

Agentic work benchmarks for GLM 5.3 and Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	Leader
AA Agentic Index	53.1	53.0	GLM 5.3
Design Arena: agents building web apps	Not measured	1248	Only Grok 4.6 measured
Design Arena: agents building full-stack apps	Not measured	1264	Only Grok 4.6 measured
Design Arena: agents building mobile apps	1194	1236	Grok 4.6
Design Arena: agents building Android apps	Not measured	1297	Only Grok 4.6 measured
Design Arena: agents building Godot games	Not measured	1276	Only Grok 4.6 measured
Design Arena: agents building games	Not measured	1208	Only Grok 4.6 measured
Design Arena: HTML slides	1189	1249	Grok 4.6
Design Arena: PowerPoint slides	1254	1241	GLM 5.3
LiveBench research	73.2%	84.5%	Grok 4.6
LiveBench browser	0.0%	64.0%	Grok 4.6
LiveBench long agentic	35.9%	40.7%	Grok 4.6
SREBench (Vals AI)	9.2%	Not measured	Only GLM 5.3 measured
Finance Agent (Vals AI)	55.8%	53.7%	GLM 5.3
Tax Agent Bench (Vals AI)	39.7%	33.1%	GLM 5.3
Legal Research Bench (Vals AI)	49.0%	48.1%	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%	62.7%	Grok 4.6
BioMysteryBench (Vals AI)	Not measured	72.2%	Only Grok 4.6 measured
Terminal-Bench-Science (Vals AI)	5.7%	11.4%	Grok 4.6
Vals Science Index	Not measured	38.1%	Only Grok 4.6 measured
Time Horizon Index (Vals AI)	Not measured	5.8%	Only Grok 4.6 measured
APEX-Agents	56.6%	65.3%	Grok 4.6
Vending-Bench 2	$8,164	$9,047	Grok 4.6
Neither model has a result on the other 17 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index47

Reasoning benchmarks for GLM 5.3 and Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	Leader
GPQA Diamond	88.1%	94.7%	Grok 4.6
LiveBench reasoning	85.8%	91.2%	Grok 4.6
MysteryMechanism (Vals AI)	23.0%	30.6%	Grok 4.6
GPQA Diamond (Artificial Analysis run)	91.7%	94.9%	Grok 4.6
Humanity's Last Exam (Artificial Analysis run)	42.3%	44.1%	Grok 4.6
GPQA Diamond (Epoch AI run)	90.9%	94.0%	Grok 4.6
ARC-AGI	Not measured	87.5%	Only Grok 4.6 measured
ARC-AGI-2	Not measured	67.1%	Only Grok 4.6 measured
SimpleBench	Not measured	75.9%	Only Grok 4.6 measured
Chess puzzles	37.0%	33.0%	GLM 5.3
Mystery game puzzles	33.0%	34.0%	Grok 4.6
EBR-bench	Not measured	30.5%	Only Grok 4.6 measured
LMArena Text: hard prompts	1490	1448	GLM 5.3
LMArena Text: expert	1514	1469	GLM 5.3
LMArena Text: hard prompts in English	1496	1445	GLM 5.3
LMArena Vision: diagrams	Not measured	1285	Only Grok 4.6 measured
LMArena Vision: homework	Not measured	1283	Only Grok 4.6 measured
Neither model has a result on the other 5 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index33

Math benchmarks for GLM 5.3 and Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	Leader
OTIS Mock AIME	91.1%	99.2%	Grok 4.6
FrontierMath, tiers 1 to 3	68.8%	66.0%	GLM 5.3
FrontierMath, tier 4	29.3%	31.7%	Grok 4.6
ProofBench	49.0%	51.0%	Grok 4.6
LMArena Text: math	1495	1417	GLM 5.3
LMArena Text: mathematical work	1497	1464	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 index54

Knowledge benchmarks for GLM 5.3 and Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	Leader
MMLU Pro	86.8%	89.4%	Grok 4.6
LegalBench (Vals AI)	84.8%	86.3%	Grok 4.6
CorpFin (Vals AI)	Not measured	66.2%	Only Grok 4.6 measured
TaxEval (Vals AI)	72.4%	71.1%	GLM 5.3
MortgageTax (Vals AI)	Not measured	64.2%	Only Grok 4.6 measured
MedCode (Vals AI)	42.9%	44.7%	Grok 4.6
SimpleQA Verified	41.0%	49.3%	Grok 4.6
LMArena Text: science	1498	1437	GLM 5.3
LMArena Text: medicine and healthcare	1481	1420	GLM 5.3
LMArena Text: legal and government	1473	1429	GLM 5.3
LMArena Text: business and finance	1459	1416	GLM 5.3
Neither model has a result on the other 7 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index63

Web design benchmarks for GLM 5.3 and Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	Leader
Design Arena: websites	1295	1289	GLM 5.3
Design Arena: UI components	1314	1295	GLM 5.3
Design Arena: game dev	1311	1296	GLM 5.3
Design Arena: data viz	1259	1282	Grok 4.6
Design Arena: 3D	1332	1277	GLM 5.3
Design Arena: all code categories	1304	1292	GLM 5.3
Design Arena: SVG	1293	1239	GLM 5.3
Design Arena: ASCII art	1213	1278	Grok 4.6
LiveBench design	77.3%	79.8%	Grok 4.6

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

General benchmarks for GLM 5.3 and Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	Leader
Vals Index	59.7%	Not measured	Only GLM 5.3 measured
LiveBench data analysis	70.2%	75.3%	Grok 4.6
Public Benefits Bench (Vals AI)	68.5%	66.8%	GLM 5.3
SAGE (Vals AI)	Not measured	28.9%	Only Grok 4.6 measured
MedScribe (Vals AI)	88.8%	86.5%	GLM 5.3
Long context reasoning (AA-LCR)	79.7%	81.0%	Grok 4.6
DTBench	87.7%	97.3%	Grok 4.6
LMCA	55.5%	48.5%	GLM 5.3
Furniture assembly	Not measured	40.0%	Only Grok 4.6 measured
LMArena Text	1474	1429	GLM 5.3
LMArena Text: instruction following	1479	1431	GLM 5.3
LMArena Text: creative writing	1458	1426	GLM 5.3
LMArena Vision	Not measured	1263	Only Grok 4.6 measured
LMArena Text: English	1482	1433	GLM 5.3
LMArena Text: non-English	1459	1420	GLM 5.3
LMArena Text: Chinese	1532	1476	GLM 5.3
LMArena Text: German	1488	1426	GLM 5.3
LMArena Text: Japanese	1460	1378	GLM 5.3
LMArena Text: Korean	1460	1391	GLM 5.3
LMArena Text: French	1503	1455	GLM 5.3
LMArena Text: Spanish	1462	1414	GLM 5.3
LMArena Text: Russian	1469	1421	GLM 5.3
LMArena Text: Polish	1466	1430	GLM 5.3
LMArena Text: multi-turn	1472	1425	GLM 5.3
LMArena Text: longer queries	1483	1456	GLM 5.3
LMArena Text: writing and language	1469	1429	GLM 5.3
LMArena Text: entertainment and media	1447	1421	GLM 5.3
LMArena Vision: English	Not measured	1270	Only Grok 4.6 measured
LMArena Vision: Chinese	Not measured	1289	Only Grok 4.6 measured
LMArena Vision: reading text	Not measured	1272	Only Grok 4.6 measured
LMArena Vision: humor	Not measured	1270	Only Grok 4.6 measured
LMArena Vision: creative writing	Not measured	1262	Only Grok 4.6 measured
LMArena Document	Not measured	1452	Only Grok 4.6 measured
Neither model has a result on the other 13 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 Grok 4.6
Benchmark	GLM 5.3	Grok 4.6	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$0.0036Fits in one request

Grok 4.6$0.0050Fits in one request

GLM 5.3 costs less

Repository review

50K input + 3K output tokens

GLM 5.3$0.083Fits in one request

Grok 4.6$0.118Fits in one request

GLM 5.3 costs less

Agent loop

200K input + 10K output tokens

GLM 5.3$0.324Fits in one request

Grok 4.6$0.460Fits 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 Grok 4.6
Specification	Z.ai GLM 5.3	SpaceXAI Grok 4.6
Maker	Z.ai	xAI
Weights	Open weights	No public weights listed
Released	August 18, 2026	August 12, 2026
Context window	1.05M	500K
Input $/Mtok	$1.40	$2.00
Output $/Mtok	$4.40	$6.00
Coding index	70.6	65.7
Independent measurements behind it	6	6
Cost per solved task	$0.36	$0.82
Source	OpenRouter listing	OpenRouter listing

Questions

Is GLM 5.3 better than Grok 4.6 for coding?

Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 65.7 for Grok 4.6. Pick Grok 4.6 for work measured by LiveBench coding or AA Coding Index, where it leads.

Which is cheaper, GLM 5.3 or Grok 4.6?

GLM 5.3 costs $1.40 per million input tokens and $4.40 per million output tokens; Grok 4.6 costs $2.00 and $6.00. Per solved SWE-bench Verified task, GLM 5.3 costs $0.36 and Grok 4.6 $0.82.

Which has the bigger context window, GLM 5.3 or Grok 4.6?

GLM 5.3, with 1.05M tokens against 500K.

How many benchmarks is the GLM 5.3 vs Grok 4.6 comparison based on?

97 benchmarks have a result for both models as of October 21, 2026. GLM 5.3's coding index rests on 6 independent benchmarks and Grok 4.6's on 6. Where only one model has a result, the page says so instead of naming a winner.

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GLM 5.3 or Grok 4.6: which to pick

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