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GLM 5.3 vs Grok 4.5

GLM 5.3 leads Grok 4.5 on coding, 70.6 to 58.6 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 22, 2026; 92 benchmarks have a result for both.

Replace GLM 5.3 Replace Grok 4.5
GLM 5.3Z.ai
Coding
70.6
Overall
67.9
Output $/M
$4.40
68
Grok 4.5xAI
Coding
58.6
Overall
62.1
Output $/M
$6.00
23
vs boards won of 92 shared, 1 tied

GLM 5.3 or Grok 4.5: which to pick

Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 58.6 for Grok 4.5.

Pick Grok 4.5 for work measured by LiveBench coding or LiveCodeBench (Vals AI), where it leads.

Model AGLM 5.3Z.ai70.6/1006 independent benchmarks$0.36 per solved taskModel BGrok 4.5xAI58.6/1006 independent benchmarks$0.62 per solved task
Shared results
92
GLM 5.3 only
8
Grok 4.5 only
31
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.

At a glance

Coding index
GLM 5.3 70.6 from 6 benchmarks, Grok 4.5 58.6 from 6 benchmarks.
Widest category
Agentic work, 11.0 points apart on average over 14 shared benchmarks.
Widest single gap
LiveBench browser: GLM 5.3 0.0% against Grok 4.5 44.0%, 44.0 points apart on a 0 to 100 scale.
Output price
GLM 5.3 $4.40 against Grok 4.5 $6.00 per million output tokens, 1.4x apart.
Context window
GLM 5.3 takes 1.05M tokens, Grok 4.5 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
CategoryGLM 5.3BarsGrok 4.5Ties
Coding174
Intelligence20
Agentic work941 tie
Reasoning45
Math51
Knowledge54
Web design63
General202
All shared boards68231 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index174
Coding benchmarks for GLM 5.3 and Grok 4.5
BenchmarkGLM 5.3Grok 4.5Leader
LiveBench coding82.8%94.3%Grok 4.5
LMArena WebDev16211553GLM 5.3
AA Coding Index74.872.4GLM 5.3
LiveCodeBench (Vals AI)80.5%87.3%Grok 4.5
SWE-bench Verified (Vals AI)95.4%86.6%GLM 5.3
Terminal-Bench 4 (Vals AI)38.9%8.6%GLM 5.3
Vibe Code Bench (Vals AI)78.1%69.0%GLM 5.3
Code migration (Vals AI)44.2%36.6%GLM 5.3
ProgramBench (Vals AI)1.5%0.0%GLM 5.3
IOI (Vals AI)68.4%40.6%GLM 5.3
Terminal-Bench 2.1 (Vals AI)71.5%67.8%GLM 5.3
Vibe Code Bench 1-100 (Vals AI)20.0%Not measuredOnly GLM 5.3 measured
SkillsBench (Vals AI)47.5%66.0%Grok 4.5
CyberBench (Vals AI)72.1%71.0%GLM 5.3
SciCode59.0%55.0%GLM 5.3
FrontierCode40.1%42.4%Grok 4.5
FrontierSWE30.2%Not measuredOnly GLM 5.3 measured
WeirdML75.4%46.4%GLM 5.3
ALE-Bench1317.41309.3GLM 5.3
LMArena Text: coding14971474GLM 5.3
LMArena Text: software and IT14931471GLM 5.3
LMArena WebDev: React16411556GLM 5.3
LMArena WebDev: HTML15951567GLM 5.3
LMArena WebDev: from an imageNot measured1562Only Grok 4.5 measured
SciCodeNot measured6.5%Only Grok 4.5 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 and Grok 4.5
BenchmarkGLM 5.3Grok 4.5Leader
AA Intelligence Index44.838.8GLM 5.3
Epoch Capabilities Index156.0154.1GLM 5.3
Agentic workLike-for-likePublic boards, shown as published, kept out of the index94
Agentic work benchmarks for GLM 5.3 and Grok 4.5
BenchmarkGLM 5.3Grok 4.5Leader
AA Agentic Index53.141.2GLM 5.3
Design Arena: agents building web appsNot measured1218Only Grok 4.5 measured
Design Arena: agents building full-stack appsNot measured1249Only Grok 4.5 measured
Design Arena: agents building mobile apps11941220Grok 4.5
Design Arena: agents building Android appsNot measured1236Only Grok 4.5 measured
Design Arena: agents building Godot gamesNot measured1229Only Grok 4.5 measured
Design Arena: agents building gamesNot measured1236Only Grok 4.5 measured
Design Arena: HTML slides11891205Grok 4.5
Design Arena: PowerPoint slides12301230Tie
LiveBench research73.2%85.9%Grok 4.5
LiveBench browser0.0%44.0%Grok 4.5
LiveBench long agentic35.9%27.9%GLM 5.3
SREBench (Vals AI)9.2%0.8%GLM 5.3
Finance Agent (Vals AI)55.8%48.4%GLM 5.3
Tax Agent Bench (Vals AI)39.7%24.9%GLM 5.3
Legal Research Bench (Vals AI)49.0%38.0%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%52.9%GLM 5.3
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly GLM 5.3 measured
Time Horizon Index (Vals AI)Not measured6.3%Only Grok 4.5 measured
APEX-Agents56.6%56.2%GLM 5.3
PostTrainBenchNot measured23.4%Only Grok 4.5 measured
Vending-Bench 2$8,164$3,887GLM 5.3
LMArena SearchNot measured1216Only Grok 4.5 measured
Neither model has a result on the other 17 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index45
Reasoning benchmarks for GLM 5.3 and Grok 4.5
BenchmarkGLM 5.3Grok 4.5Leader
GPQA Diamond88.1%92.9%Grok 4.5
LiveBench reasoning85.8%87.2%Grok 4.5
MysteryMechanism (Vals AI)23.0%Not measuredOnly GLM 5.3 measured
MMMU Pro (Vals AI)Not measured61.8%Only Grok 4.5 measured
GPQA Diamond (Artificial Analysis run)91.7%93.1%Grok 4.5
Humanity's Last Exam (Artificial Analysis run)42.3%42.7%Grok 4.5
GPQA Diamond (Epoch AI run)90.9%93.4%Grok 4.5
ARC-AGINot measured87.2%Only Grok 4.5 measured
ARC-AGI-2Not measured52.6%Only Grok 4.5 measured
SimpleBenchNot measured70.0%Only Grok 4.5 measured
Chess puzzles37.0%35.0%GLM 5.3
Mystery game puzzles33.0%Not measuredOnly GLM 5.3 measured
LMArena Text: hard prompts14901462GLM 5.3
LMArena Text: expert15141465GLM 5.3
LMArena Text: hard prompts in English14961464GLM 5.3
LMArena Vision: diagramsNot measured1304Only Grok 4.5 measured
LMArena Vision: homeworkNot measured1295Only Grok 4.5 measured
Kagi LLM BenchmarkNot measured83.5%Only Grok 4.5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index51
Math benchmarks for GLM 5.3 and Grok 4.5
BenchmarkGLM 5.3Grok 4.5Leader
OTIS Mock AIME91.1%97.8%Grok 4.5
FrontierMath, tiers 1 to 368.8%57.2%GLM 5.3
FrontierMath, tier 429.3%24.4%GLM 5.3
ProofBench49.0%31.0%GLM 5.3
LMArena Text: math14951460GLM 5.3
LMArena Text: mathematical work14971482GLM 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 4.5
BenchmarkGLM 5.3Grok 4.5Leader
MMLU Pro86.8%89.2%Grok 4.5
LegalBench (Vals AI)84.8%86.0%Grok 4.5
CorpFin (Vals AI)Not measured67.4%Only Grok 4.5 measured
TaxEval (Vals AI)72.4%71.7%GLM 5.3
MortgageTax (Vals AI)Not measured61.8%Only Grok 4.5 measured
MedCode (Vals AI)42.9%43.3%Grok 4.5
SimpleQA Verified41.0%48.3%Grok 4.5
LMArena Text: science14981464GLM 5.3
LMArena Text: medicine and healthcare14811440GLM 5.3
LMArena Text: legal and government14731463GLM 5.3
LMArena Text: business and finance14591441GLM 5.3
FACTS Benchmark SuiteNot measured50.2%Only Grok 4.5 measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index63
Web design benchmarks for GLM 5.3 and Grok 4.5
BenchmarkGLM 5.3Grok 4.5Leader
Design Arena: websites12951281GLM 5.3
Design Arena: UI components13141280GLM 5.3
Design Arena: game dev13111264GLM 5.3
Design Arena: data viz12601266Grok 4.5
Design Arena: 3D13321257GLM 5.3
Design Arena: all code categories13041275GLM 5.3
Design Arena: SVG12941215GLM 5.3
Design Arena: ASCII art12081256Grok 4.5
LiveBench design77.3%78.1%Grok 4.5
GeneralLike-for-likePublic boards, shown as published, kept out of the index202
General benchmarks for GLM 5.3 and Grok 4.5
BenchmarkGLM 5.3Grok 4.5Leader
Vals Index59.7%Not measuredOnly GLM 5.3 measured
LiveBench data analysis70.2%73.0%Grok 4.5
Public Benefits Bench (Vals AI)68.5%Not measuredOnly GLM 5.3 measured
SAGE (Vals AI)Not measured35.0%Only Grok 4.5 measured
MedScribe (Vals AI)88.8%86.9%GLM 5.3
Vals Multimodal IndexNot measured63.4%Only Grok 4.5 measured
Long context reasoning (AA-LCR)79.7%79.3%GLM 5.3
DTBench87.7%96.5%Grok 4.5
LMCA55.5%45.2%GLM 5.3
Surface Evolver BenchNot measured74.4%Only Grok 4.5 measured
Furniture assemblyNot measured22.5%Only Grok 4.5 measured
LMArena Text14741448GLM 5.3
LMArena Text: instruction following14791445GLM 5.3
LMArena Text: creative writing14581442GLM 5.3
LMArena VisionNot measured1287Only Grok 4.5 measured
LMArena Text: English14821453GLM 5.3
LMArena Text: non-English14591440GLM 5.3
LMArena Text: Chinese15321495GLM 5.3
LMArena Text: German14881448GLM 5.3
LMArena Text: Japanese14601430GLM 5.3
LMArena Text: Korean14601406GLM 5.3
LMArena Text: French15031457GLM 5.3
LMArena Text: Spanish14621451GLM 5.3
LMArena Text: Russian14691449GLM 5.3
LMArena Text: Polish14661432GLM 5.3
LMArena Text: multi-turn14721456GLM 5.3
LMArena Text: longer queries14831462GLM 5.3
LMArena Text: writing and language14691445GLM 5.3
LMArena Text: entertainment and media14471434GLM 5.3
LMArena Vision: EnglishNot measured1285Only Grok 4.5 measured
LMArena Vision: ChineseNot measured1345Only Grok 4.5 measured
LMArena Vision: reading textNot measured1293Only Grok 4.5 measured
LMArena Vision: humorNot measured1276Only Grok 4.5 measured
LMArena Vision: creative writingNot measured1293Only Grok 4.5 measured
LMArena DocumentNot measured1452Only Grok 4.5 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 Grok 4.5
BenchmarkGLM 5.3Grok 4.5Leader
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 4.5$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 4.5$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 4.5$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 4.5
SpecificationZ.ai GLM 5.3SpaceXAI Grok 4.5
MakerZ.aixAI
WeightsOpen weightsNo public weights listed
ReleasedAugust 18, 2026July 8, 2026
Context window1.05M500K
Input $/Mtok$1.40$2.00
Output $/Mtok$4.40$6.00
Coding index70.658.6
Independent measurements behind it66
Cost per solved task$0.36$0.62
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 better than Grok 4.5 for coding?

Pick GLM 5.3 for coding: it scores 70.6 on the Vibe Coding Index against 58.6 for Grok 4.5. Pick Grok 4.5 for work measured by LiveBench coding or LiveCodeBench (Vals AI), where it leads.

Which is cheaper, GLM 5.3 or Grok 4.5?

GLM 5.3 costs $1.40 per million input tokens and $4.40 per million output tokens; Grok 4.5 costs $2.00 and $6.00. Per solved SWE-bench Verified task, GLM 5.3 costs $0.36 and Grok 4.5 $0.62.

Which has the bigger context window, GLM 5.3 or Grok 4.5?

GLM 5.3, with 1.05M tokens against 500K.

How many benchmarks is the GLM 5.3 vs Grok 4.5 comparison based on?

92 benchmarks have a result for both models as of October 22, 2026. GLM 5.3's coding index rests on 6 independent benchmarks and Grok 4.5's on 6. Where only one model has a result, the page says so instead of naming a winner.

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