LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

GLM 5.3 vs Grok 4.3

Updated October 21, 2026. 79 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 Grok 4.3
GLM 5.3Z.ai
Coding
73.1
Overall
44.8
Output $/M
$1.40
75
Grok 4.3xAI
Coding
22.5
Overall
24.9
Output $/M
$2.50
4
vs boards won of 79 shared

Decision reading

Pick GLM 5.3 for coding: it scores 73.1 on the Vibe Coding Index against 22.5 for Grok 4.3.

Pick Grok 4.3 when a solved task costs $0.31 against $0.36, or when what matters is LiveCodeBench (Vals AI) or GPQA Diamond, where it leads.

Model AGLM 5.3Z.ai73.1/1002 independent benchmarks$0.36 per solved taskModel BGrok 4.3xAI22.5/1001 independent benchmark$0.31 per solved task
Shared results
79
GLM 5.3 only
21
Grok 4.3 only
25
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.

At a glance

Coding index
GLM 5.3 73.1 from 2 benchmarks, Grok 4.3 22.5 from 1 benchmark.
Widest category
Agentic work, 31.3 points apart on average over 9 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): GLM 5.3 78.1% against Grok 4.3 19.4%, 58.7 points apart on a 0 to 100 scale.
Output price
GLM 5.3 $1.40 against Grok 4.3 $2.50 per million output tokens, 1.8x apart.
Context window
GLM 5.3 takes 1.05M tokens, Grok 4.3 1M.

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 5.3BarsGrok 4.3Ties
Coding151
Intelligence10
Agentic work90
Reasoning71
Math51
Knowledge90
Web design80
General211
All shared boards754
CodingLike-for-likeFour of these boards feed the Vibe Coding Index151
Coding benchmarks for GLM 5.3 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
LiveBench coding82.8%Not measuredOnly GLM 5.3 measured
LMArena WebDev16211358GLM 5.3
AA Coding Index74.842.2GLM 5.3
LiveCodeBench (Vals AI)80.5%84.5%Grok 4.3
SWE-bench Verified (Vals AI)95.4%71.4%GLM 5.3
Terminal-Bench 4 (Vals AI)38.9%Not measuredOnly GLM 5.3 measured
Vibe Code Bench (Vals AI)78.1%19.4%GLM 5.3
Code migration (Vals AI)44.2%6.8%GLM 5.3
ProgramBench (Vals AI)1.5%0.0%GLM 5.3
IOI (Vals AI)68.4%Not measuredOnly GLM 5.3 measured
Terminal-Bench 2.1 (Vals AI)71.5%42.0%GLM 5.3
Vibe Code Bench 1-100 (Vals AI)20.0%Not measuredOnly GLM 5.3 measured
SkillsBench (Vals AI)47.5%40.6%GLM 5.3
CyberBench (Vals AI)72.1%Not measuredOnly GLM 5.3 measured
SciCode59.0%48.3%GLM 5.3
Terminal-Bench Hard (Artificial Analysis run)Not measured37.9%Only Grok 4.3 measured
FrontierCode40.1%Not measuredOnly GLM 5.3 measured
FrontierSWE30.2%Not measuredOnly GLM 5.3 measured
WeirdML75.4%49.9%GLM 5.3
ALE-Bench1317.4944.2GLM 5.3
LMArena Text: coding14971415GLM 5.3
LMArena Text: software and IT14931416GLM 5.3
LMArena WebDev: React16411353GLM 5.3
LMArena WebDev: HTML15951367GLM 5.3
LMArena WebDev: from an imageNot measured1375Only Grok 4.3 measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.3 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
AA Intelligence Index44.824.9GLM 5.3
Epoch Capabilities Index156.0Not measuredOnly GLM 5.3 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index90
Agentic work benchmarks for GLM 5.3 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
AA Agentic Index53.115.5GLM 5.3
Design Arena: agents building web appsNot measured1126Only Grok 4.3 measured
Design Arena: agents building full-stack appsNot measured1006Only Grok 4.3 measured
Design Arena: agents building mobile apps11941059GLM 5.3
Design Arena: agents building Android appsNot measured967Only Grok 4.3 measured
Design Arena: agents building Godot gamesNot measured914Only Grok 4.3 measured
Design Arena: agents building gamesNot measured1007Only Grok 4.3 measured
Design Arena: HTML slides11891008GLM 5.3
Design Arena: PowerPoint slides12551012GLM 5.3
LiveBench research73.2%Not measuredOnly GLM 5.3 measured
LiveBench browser0.0%Not measuredOnly GLM 5.3 measured
LiveBench long agentic35.9%Not measuredOnly GLM 5.3 measured
SREBench (Vals AI)9.2%Not measuredOnly GLM 5.3 measured
Finance Agent (Vals AI)55.8%37.7%GLM 5.3
Tax Agent Bench (Vals AI)39.7%6.2%GLM 5.3
Legal Research Bench (Vals AI)49.0%15.4%GLM 5.3
Harvey's Legal Agent Benchmark (Vals AI)14.6%Not measuredOnly GLM 5.3 measured
Excel Modeling Benchmark (Vals AI)56.3%18.4%GLM 5.3
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly GLM 5.3 measured
τ²-Bench TelecomNot measured97.7%Only Grok 4.3 measured
APEX-Agents56.6%Not measuredOnly GLM 5.3 measured
Vending-Bench 2$8,164$35GLM 5.3
LMArena SearchNot measured1166Only Grok 4.3 measured
Neither model has a result on the other 16 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index71
Reasoning benchmarks for GLM 5.3 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
GPQA Diamond88.1%91.4%Grok 4.3
LiveBench reasoning85.8%Not measuredOnly GLM 5.3 measured
MysteryMechanism (Vals AI)23.0%Not measuredOnly GLM 5.3 measured
MMMU Pro (Vals AI)Not measured83.1%Only Grok 4.3 measured
GPQA Diamond (Artificial Analysis run)91.7%90.1%GLM 5.3
Humanity's Last Exam (Artificial Analysis run)42.3%37.2%GLM 5.3
GPQA Diamond (Epoch AI run)90.9%88.8%GLM 5.3
Chess puzzles37.0%18.0%GLM 5.3
Mystery game puzzles33.0%Not measuredOnly GLM 5.3 measured
LMArena Text: hard prompts14901396GLM 5.3
LMArena Text: expert15141384GLM 5.3
LMArena Text: hard prompts in English14961402GLM 5.3
LMArena Vision: diagramsNot measured1241Only Grok 4.3 measured
LMArena Vision: homeworkNot measured1241Only Grok 4.3 measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index51
Math benchmarks for GLM 5.3 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
OTIS Mock AIME91.1%93.3%Grok 4.3
FrontierMath, tiers 1 to 368.8%42.8%GLM 5.3
FrontierMath, tier 429.3%14.6%GLM 5.3
ProofBench49.0%11.0%GLM 5.3
LMArena Text: math14951387GLM 5.3
LMArena Text: mathematical work14971396GLM 5.3
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index90
Knowledge benchmarks for GLM 5.3 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
MMLU Pro86.8%85.8%GLM 5.3
LegalBench (Vals AI)84.8%84.5%GLM 5.3
CaseLaw (Vals AI)Not measured79.3%Only Grok 4.3 measured
CorpFin (Vals AI)Not measured68.5%Only Grok 4.3 measured
TaxEval (Vals AI)72.4%70.8%GLM 5.3
MortgageTax (Vals AI)Not measured48.3%Only Grok 4.3 measured
MedCode (Vals AI)42.9%38.1%GLM 5.3
SimpleQA Verified41.0%33.2%GLM 5.3
LMArena Text: science14981399GLM 5.3
LMArena Text: medicine and healthcare14811384GLM 5.3
LMArena Text: legal and government14731386GLM 5.3
LMArena Text: business and finance14591381GLM 5.3
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for GLM 5.3 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
Design Arena: websites12951196GLM 5.3
Design Arena: UI components13141192GLM 5.3
Design Arena: game dev13111174GLM 5.3
Design Arena: data viz12601180GLM 5.3
Design Arena: 3D13321125GLM 5.3
Design Arena: all code categories13041187GLM 5.3
Design Arena: SVG12921081GLM 5.3
Design Arena: ASCII art12131125GLM 5.3
LiveBench design77.3%Not measuredOnly GLM 5.3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index211
General benchmarks for GLM 5.3 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
Vals Index59.7%Not measuredOnly GLM 5.3 measured
LiveBench data analysis70.2%Not measuredOnly GLM 5.3 measured
Public Benefits Bench (Vals AI)68.5%51.7%GLM 5.3
SAGE (Vals AI)Not measured19.7%Only Grok 4.3 measured
MedScribe (Vals AI)88.8%74.4%GLM 5.3
Vals Multimodal IndexNot measured43.3%Only Grok 4.3 measured
IFBenchNot measured83.3%Only Grok 4.3 measured
Long context reasoning (AA-LCR)79.7%75.0%GLM 5.3
DTBench87.7%90.7%Grok 4.3
LMCA55.5%38.3%GLM 5.3
LMArena Text14741397GLM 5.3
LMArena Text: instruction following14791366GLM 5.3
LMArena Text: creative writing14581380GLM 5.3
LMArena VisionNot measured1229Only Grok 4.3 measured
LMArena Text: English14821404GLM 5.3
LMArena Text: non-English14591385GLM 5.3
LMArena Text: Chinese15321422GLM 5.3
LMArena Text: German14881395GLM 5.3
LMArena Text: Japanese14601379GLM 5.3
LMArena Text: Korean14601354GLM 5.3
LMArena Text: French15031411GLM 5.3
LMArena Text: Spanish14621399GLM 5.3
LMArena Text: Russian14691399GLM 5.3
LMArena Text: Polish14661398GLM 5.3
LMArena Text: multi-turn14721406GLM 5.3
LMArena Text: longer queries14831393GLM 5.3
LMArena Text: writing and language14691385GLM 5.3
LMArena Text: entertainment and media14471370GLM 5.3
LMArena Vision: EnglishNot measured1235Only Grok 4.3 measured
LMArena Vision: ChineseNot measured1257Only Grok 4.3 measured
LMArena Vision: reading textNot measured1235Only Grok 4.3 measured
LMArena Vision: humorNot measured1222Only Grok 4.3 measured
LMArena Vision: recognizing thingsNot measured1217Only Grok 4.3 measured
LMArena Vision: creative writingNot measured1237Only Grok 4.3 measured
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 and Grok 4.3
BenchmarkGLM 5.3Grok 4.3Leader
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
Grok 4.3$0.0025Fits in one request

GLM 5.3 costs less

Repository review

50K input + 3K output tokens

GLM 5.3$0.0081Fits in one request
Grok 4.3$0.070Fits in one request

GLM 5.3 costs less

Agent loop

200K input + 10K output tokens

GLM 5.3$0.030Fits in one request
Grok 4.3$0.275Fits 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 4.3
SpecificationZ.ai GLM 5.3SpaceXAI Grok 4.3
MakerZ.aixAI
WeightsOpen weightsNo public weights listed
ReleasedAugust 18, 2026April 30, 2026
Context window1.05M1M
Input $/Mtok$0.079$1.25
Output $/Mtok$1.40$2.50
Coding index73.122.5
Independent measurements behind it21
Cost per solved task$0.36$0.31
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 better than Grok 4.3 for coding?

Pick GLM 5.3 for coding: it scores 73.1 on the Vibe Coding Index against 22.5 for Grok 4.3. Pick Grok 4.3 when a solved task costs $0.31 against $0.36, or when what matters is LiveCodeBench (Vals AI) or GPQA Diamond, where it leads.

Which is cheaper, GLM 5.3 or Grok 4.3?

GLM 5.3 costs $0.079 per million input tokens and $1.40 per million output tokens; Grok 4.3 costs $1.25 and $2.50. Per solved SWE-bench Verified task, GLM 5.3 costs $0.36 and Grok 4.3 $0.31.

Which has the bigger context window, GLM 5.3 or Grok 4.3?

GLM 5.3, with 1.05M tokens against 1M.

How many benchmarks is the GLM 5.3 vs Grok 4.3 comparison based on?

79 benchmarks have a result for both models as of October 21, 2026. GLM 5.3's coding index rests on 2 independent benchmarks and Grok 4.3's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next