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Claude Opus 4.5 vs GLM 5.3

Updated October 21, 2026. 66 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Claude Opus 4.5 Replace GLM 5.3
Claude Opus 4.5Anthropic
Coding
66.8
Overall
29.1
Output $/M
$25.00
7
GLM 5.3Z.ai
Coding
73.1
Overall
44.8
Output $/M
$1.40
59
vs boards won of 66 shared

Decision reading

Pick GLM 5.3 for coding: it scores 73.1 on the Vibe Coding Index against 66.8 for Claude Opus 4.5.

Pick Claude Opus 4.5 when what matters is LiveCodeBench (Vals AI) or LMArena Text: coding, where it leads.

Model AClaude Opus 4.5Anthropic66.8/1002 independent benchmarks$1.37 per solved taskModel BGLM 5.3Z.ai73.1/1002 independent benchmarks$0.36 per solved task
Shared results
66
Claude Opus 4.5 only
39
GLM 5.3 only
34
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
Claude Opus 4.5 66.8 from 2 benchmarks, GLM 5.3 73.1 from 2 benchmarks.
Widest category
Coding, 16.3 points apart on average over 9 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Claude Opus 4.5 20.6% against GLM 5.3 78.1%, 57.5 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.5 $25.00 against GLM 5.3 $1.40 per million output tokens, 17.9x apart.
Context window
Claude Opus 4.5 takes 200K tokens, GLM 5.3 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
CategoryClaude Opus 4.5BarsGLM 5.3Ties
Coding27
Intelligence02
Agentic work02
Reasoning09
Math06
Knowledge45
Web design08
General120
All shared boards759
CodingLike-for-likeFour of these boards feed the Vibe Coding Index27
Coding benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
SWE-bench Verified79.2%Not measuredOnly Claude Opus 4.5 measured
SWE-bench (full test set)52.6%Not measuredOnly Claude Opus 4.5 measured
SWE-bench Multilingual70.7%Not measuredOnly Claude Opus 4.5 measured
LiveBench codingNot measured82.8%Only GLM 5.3 measured
LMArena WebDev14941621GLM 5.3
AA Coding IndexNot measured74.8Only GLM 5.3 measured
LiveCodeBench (Vals AI)83.7%80.5%Claude Opus 4.5
SWE-bench Verified (Vals AI)76.4%95.4%GLM 5.3
Terminal-Bench 4 (Vals AI)Not measured38.9%Only GLM 5.3 measured
Vibe Code Bench (Vals AI)20.6%78.1%GLM 5.3
Code migration (Vals AI)Not measured44.2%Only GLM 5.3 measured
ProgramBench (Vals AI)Not measured1.5%Only GLM 5.3 measured
IOI (Vals AI)Not measured68.4%Only GLM 5.3 measured
Terminal-Bench 2.1 (Vals AI)Not measured71.5%Only GLM 5.3 measured
Vibe Code Bench 1-100 (Vals AI)Not measured20.0%Only GLM 5.3 measured
SkillsBench (Vals AI)Not measured47.5%Only GLM 5.3 measured
CyberBench (Vals AI)Not measured72.1%Only GLM 5.3 measured
LiveCodeBench (Artificial Analysis run)87.1%Not measuredOnly Claude Opus 4.5 measured
SciCodeNot measured59.0%Only GLM 5.3 measured
Terminal-Bench Hard (Artificial Analysis run)47.0%Not measuredOnly Claude Opus 4.5 measured
Terminal-Bench63.1%Not measuredOnly Claude Opus 4.5 measured
FrontierCodeNot measured40.1%Only GLM 5.3 measured
FrontierSWENot measured30.2%Only GLM 5.3 measured
GSO-Bench26.5%Not measuredOnly Claude Opus 4.5 measured
WeirdML63.7%75.4%GLM 5.3
Cybench82.0%Not measuredOnly Claude Opus 4.5 measured
ALE-BenchNot measured1317.4Only GLM 5.3 measured
LMArena Text: coding15031497Claude Opus 4.5
LMArena Text: software and IT14831493GLM 5.3
LMArena WebDev: React14781641GLM 5.3
LMArena WebDev: HTML15101595GLM 5.3
Neither model has a result on the other 7 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
AA Intelligence Index29.144.8GLM 5.3
Epoch Capabilities Index150.1156.0GLM 5.3
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
AA Agentic IndexNot measured53.1Only GLM 5.3 measured
Design Arena: agents building web apps1159Not measuredOnly Claude Opus 4.5 measured
Design Arena: agents building full-stack apps1156Not measuredOnly Claude Opus 4.5 measured
Design Arena: agents building mobile apps11891194GLM 5.3
Design Arena: agents building Android apps1181Not measuredOnly Claude Opus 4.5 measured
Design Arena: HTML slidesNot measured1189Only GLM 5.3 measured
Design Arena: PowerPoint slidesNot measured1255Only GLM 5.3 measured
LiveBench researchNot measured73.2%Only GLM 5.3 measured
LiveBench browserNot measured0.0%Only GLM 5.3 measured
LiveBench long agenticNot measured35.9%Only GLM 5.3 measured
SREBench (Vals AI)Not measured9.2%Only GLM 5.3 measured
Finance Agent (Vals AI)Not measured55.8%Only GLM 5.3 measured
Tax Agent Bench (Vals AI)Not measured39.7%Only GLM 5.3 measured
Legal Research Bench (Vals AI)Not measured49.0%Only GLM 5.3 measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured14.6%Only GLM 5.3 measured
Excel Modeling Benchmark (Vals AI)Not measured56.3%Only GLM 5.3 measured
Terminal-Bench-Science (Vals AI)Not measured5.7%Only GLM 5.3 measured
τ²-Bench Telecom89.5%Not measuredOnly Claude Opus 4.5 measured
APEX-AgentsNot measured56.6%Only GLM 5.3 measured
METR time horizons75.0%Not measuredOnly Claude Opus 4.5 measured
Remote Labor Index3.8%Not measuredOnly Claude Opus 4.5 measured
GDPval45.5%Not measuredOnly Claude Opus 4.5 measured
BALROG43.5%Not measuredOnly Claude Opus 4.5 measured
DeepResearch Bench54.8%Not measuredOnly Claude Opus 4.5 measured
OSWorld66.3%Not measuredOnly Claude Opus 4.5 measured
Vending-Bench 2$4,967$8,164GLM 5.3
Neither model has a result on the other 13 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
GPQA Diamond85.9%88.1%GLM 5.3
LiveBench reasoningNot measured85.8%Only GLM 5.3 measured
MysteryMechanism (Vals AI)Not measured23.0%Only GLM 5.3 measured
MMMU Pro (Vals AI)83.0%Not measuredOnly Claude Opus 4.5 measured
GPQA Diamond (Artificial Analysis run)86.6%91.7%GLM 5.3
Humanity's Last Exam (Artificial Analysis run)30.1%42.3%GLM 5.3
GPQA Diamond (Epoch AI run)86.0%90.9%GLM 5.3
ARC-AGI80.0%Not measuredOnly Claude Opus 4.5 measured
ARC-AGI-237.6%Not measuredOnly Claude Opus 4.5 measured
SimpleBench62.0%Not measuredOnly Claude Opus 4.5 measured
Chess puzzles14.0%37.0%GLM 5.3
Mystery game puzzles22.0%33.0%GLM 5.3
EBR-bench14.3%Not measuredOnly Claude Opus 4.5 measured
VPCT40.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: hard prompts14761490GLM 5.3
LMArena Text: expert14871514GLM 5.3
LMArena Text: hard prompts in English14821496GLM 5.3
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index06
Math benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
AIME95.4%Not measuredOnly Claude Opus 4.5 measured
MGSM (Vals AI)95.2%Not measuredOnly Claude Opus 4.5 measured
AA Math Index91.3Not measuredOnly Claude Opus 4.5 measured
AIME 2025 (Artificial Analysis run)91.3%Not measuredOnly Claude Opus 4.5 measured
OTIS Mock AIME86.1%91.1%GLM 5.3
FrontierMath, tiers 1 to 334.4%68.8%GLM 5.3
FrontierMath, tier 44.9%29.3%GLM 5.3
ProofBench36.0%49.0%GLM 5.3
LMArena Text: math14631495GLM 5.3
LMArena Text: mathematical work14681497GLM 5.3
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index45
Knowledge benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
MMLU Pro87.3%86.8%Claude Opus 4.5
LegalBench (Vals AI)84.6%84.8%GLM 5.3
CaseLaw (Vals AI)62.6%Not measuredOnly Claude Opus 4.5 measured
CorpFin (Vals AI)65.1%Not measuredOnly Claude Opus 4.5 measured
TaxEval (Vals AI)74.9%72.4%Claude Opus 4.5
MortgageTax (Vals AI)68.7%Not measuredOnly Claude Opus 4.5 measured
MedQA (Vals AI)95.9%Not measuredOnly Claude Opus 4.5 measured
MedCode (Vals AI)49.2%42.9%Claude Opus 4.5
MMLU Pro (Artificial Analysis run)89.5%Not measuredOnly Claude Opus 4.5 measured
SimpleQA Verified45.7%41.0%Claude Opus 4.5
GeoBench75.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: science14541498GLM 5.3
LMArena Text: medicine and healthcare14441481GLM 5.3
LMArena Text: legal and government14591473GLM 5.3
LMArena Text: business and finance14481459GLM 5.3
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
Design Arena: websites12471295GLM 5.3
Design Arena: UI components12381314GLM 5.3
Design Arena: game dev12291311GLM 5.3
Design Arena: data viz12431260GLM 5.3
Design Arena: 3D12141332GLM 5.3
Design Arena: all code categories12421304GLM 5.3
Design Arena: SVG11801292GLM 5.3
Design Arena: ASCII art11901213GLM 5.3
LiveBench designNot measured77.3%Only GLM 5.3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
General benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
Vals IndexNot measured59.7%Only GLM 5.3 measured
LiveBench data analysisNot measured70.2%Only GLM 5.3 measured
Public Benefits Bench (Vals AI)Not measured68.5%Only GLM 5.3 measured
SAGE (Vals AI)52.1%Not measuredOnly Claude Opus 4.5 measured
MedScribe (Vals AI)85.3%88.8%GLM 5.3
IFBench58.0%Not measuredOnly Claude Opus 4.5 measured
Long context reasoning (AA-LCR)77.3%79.7%GLM 5.3
DTBench89.9%87.7%Claude Opus 4.5
LMCA44.5%55.5%GLM 5.3
CL-bench21.1%Not measuredOnly Claude Opus 4.5 measured
Furniture assembly28.3%Not measuredOnly Claude Opus 4.5 measured
LMArena Text14511474GLM 5.3
LMArena Text: instruction following14781479GLM 5.3
LMArena Text: creative writing14451458GLM 5.3
LMArena Text: English14611482GLM 5.3
LMArena Text: non-English14381459GLM 5.3
LMArena Text: Chinese14701532GLM 5.3
LMArena Text: German14491488GLM 5.3
LMArena Text: Japanese14171460GLM 5.3
LMArena Text: Korean14241460GLM 5.3
LMArena Text: French14711503GLM 5.3
LMArena Text: Spanish14571462GLM 5.3
LMArena Text: Russian14471469GLM 5.3
LMArena Text: Polish14391466GLM 5.3
LMArena Text: multi-turn14661472GLM 5.3
LMArena Text: longer queries14791483GLM 5.3
LMArena Text: writing and language14521469GLM 5.3
LMArena Text: entertainment and media14341447GLM 5.3
LMArena Document1462Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.5 and GLM 5.3
BenchmarkClaude Opus 4.5GLM 5.3Leader
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

Claude Opus 4.5$0.018Fits in one request
GLM 5.3$0.0008Fits in one request

GLM 5.3 costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.5$0.325Fits in one request
GLM 5.3$0.0081Fits in one request

GLM 5.3 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.5$1.25Exceeds the context window
GLM 5.3$0.030Fits 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 Claude Opus 4.5 and GLM 5.3
SpecificationAnthropic Claude Opus 4.5Z.ai GLM 5.3
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedNovember 24, 2025August 18, 2026
Context window200K1.05M
Input $/Mtok$5.00$0.079
Output $/Mtok$25.00$1.40
Coding index66.873.1
Independent measurements behind it22
Cost per solved task$1.37$0.36
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.5 better than GLM 5.3 for coding?

Pick GLM 5.3 for coding: it scores 73.1 on the Vibe Coding Index against 66.8 for Claude Opus 4.5. Pick Claude Opus 4.5 when what matters is LiveCodeBench (Vals AI) or LMArena Text: coding, where it leads.

Which is cheaper, Claude Opus 4.5 or GLM 5.3?

Claude Opus 4.5 costs $5.00 per million input tokens and $25.00 per million output tokens; GLM 5.3 costs $0.079 and $1.40. Per solved SWE-bench Verified task, Claude Opus 4.5 costs $1.37 and GLM 5.3 $0.36.

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

GLM 5.3, with 1.05M tokens against 200K.

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

66 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.5's coding index rests on 2 independent benchmarks and GLM 5.3's on 2. Where only one model has a result, the page says so instead of naming a winner.

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