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Claude Opus 4.8 vs GLM 5.3 Flash

Claude Opus 4.8 leads GLM 5.3 Flash on coding, 65.0 to 57.7 on the Vibe Coding Index, and GLM 5.3 Flash costs 50.0x less per output token ($0.50 vs $25.00 per million). Updated October 22, 2026; 93 benchmarks have a result for both.

Replace Claude Opus 4.8 Replace GLM 5.3 Flash
Claude Opus 4.8Anthropic
Coding
65.0
Overall
69.8
Output $/M
$25.00
48
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
44
vs boards won of 93 shared, 1 tied

Claude Opus 4.8 or GLM 5.3 Flash: which to pick

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 57.7 for GLM 5.3 Flash.

Pick GLM 5.3 Flash for output tokens 50.0x cheaper ($0.50 vs $25.00 per million) and a lower cost per solved task ($0.02 against $2.17).

Model AClaude Opus 4.8Anthropic65.0/1006 independent benchmarks$2.17 per solved taskModel BGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved task
Shared results
93
Claude Opus 4.8 only
37
GLM 5.3 Flash only
9
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
Claude Opus 4.8 65.0 from 6 benchmarks, GLM 5.3 Flash 57.7 from 6 benchmarks.
Widest category
Math, 19.8 points apart on average over 6 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Claude Opus 4.8 82.7% against GLM 5.3 Flash 30.8%, 52.0 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against GLM 5.3 Flash $0.50 per million output tokens, 50.0x apart.
Context window
Claude Opus 4.8 takes 1M tokens, GLM 5.3 Flash 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 4.8BarsGLM 5.3 FlashTies
Coding98
Intelligence101 tie
Agentic work55
Reasoning114
Math51
Knowledge34
Web design27
General1215
All shared boards48441 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index98
Coding benchmarks for Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
LiveBench coding77.3%80.6%GLM 5.3 Flash
LMArena WebDev15561607GLM 5.3 Flash
AA Coding Index74.371.5Claude Opus 4.8
LiveCodeBench (Vals AI)87.8%80.5%Claude Opus 4.8
SWE-bench Verified (Vals AI)88.6%92.0%GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)23.2%37.4%GLM 5.3 Flash
Vibe Code Bench (Vals AI)82.7%30.8%Claude Opus 4.8
Code migration (Vals AI)47.3%20.5%Claude Opus 4.8
ProgramBench (Vals AI)1.0%0.0%Claude Opus 4.8
IOI (Vals AI)Not measured52.5%Only GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)71.9%62.9%Claude Opus 4.8
Vibe Code Bench 1-100 (Vals AI)Not measured16.0%Only GLM 5.3 Flash measured
SkillsBench (Vals AI)59.2%40.2%Claude Opus 4.8
CyberBench (Vals AI)Not measured67.9%Only GLM 5.3 Flash measured
SciCode54.4%51.6%Claude Opus 4.8
Terminal-Bench Hard (Artificial Analysis run)58.3%Not measuredOnly Claude Opus 4.8 measured
FrontierCode46.5%31.8%Claude Opus 4.8
FrontierSWENot measured18.1%Only GLM 5.3 Flash measured
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%Not measuredOnly Claude Opus 4.8 measured
ALE-BenchNot measured303.6Only GLM 5.3 Flash measured
LMArena Text: coding14901507GLM 5.3 Flash
LMArena Text: software and IT14881500GLM 5.3 Flash
LMArena WebDev: React15571624GLM 5.3 Flash
LMArena WebDev: HTML15431577GLM 5.3 Flash
LMArena WebDev: from an imageNot measured1578Only GLM 5.3 Flash measured
SciCode12.3%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 12 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
AA Intelligence Index41.841.8Tie
Epoch Capabilities Index159.0153.1Claude Opus 4.8
Agentic workLike-for-likePublic boards, shown as published, kept out of the index55
Agentic work benchmarks for Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
AA Agentic Index41.950.9GLM 5.3 Flash
Design Arena: agents building web apps1233Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building full-stack apps1249Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building mobile apps1222Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Android apps1233Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building Godot games1231Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building games1239Not measuredOnly Claude Opus 4.8 measured
Design Arena: HTML slides1171Not measuredOnly Claude Opus 4.8 measured
Design Arena: PowerPoint slides1202Not measuredOnly Claude Opus 4.8 measured
Design Arena: spreadsheets1303Not measuredOnly Claude Opus 4.8 measured
LiveBench research81.8%70.1%Claude Opus 4.8
LiveBench browser96.0%84.0%Claude Opus 4.8
LiveBench long agentic48.3%28.4%Claude Opus 4.8
SREBench (Vals AI)Not measured0.8%Only GLM 5.3 Flash measured
Finance Agent (Vals AI)53.9%57.9%GLM 5.3 Flash
Tax Agent Bench (Vals AI)30.0%31.6%GLM 5.3 Flash
Legal Research Bench (Vals AI)43.8%45.2%GLM 5.3 Flash
Harvey's Legal Agent Benchmark (Vals AI)Not measured10.4%Only GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)69.4%55.9%Claude Opus 4.8
Terminal-Bench-Science (Vals AI)4.3%2.9%Claude Opus 4.8
Time Horizon Index (Vals AI)11.8%Not measuredOnly Claude Opus 4.8 measured
τ²-Bench Telecom94.4%Not measuredOnly Claude Opus 4.8 measured
APEX-Agents48.9%52.8%GLM 5.3 Flash
Remote Labor Index8.3%Not measuredOnly Claude Opus 4.8 measured
OSWorld 2.020.6%Not measuredOnly Claude Opus 4.8 measured
DeepResearch Bench50.2%Not measuredOnly Claude Opus 4.8 measured
PostTrainBench33.8%Not measuredOnly Claude Opus 4.8 measured
Vending-Bench 2$5,787Not measuredOnly Claude Opus 4.8 measured
LMArena Search1204Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 12 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index114
Reasoning benchmarks for Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
GPQA Diamond92.4%86.4%Claude Opus 4.8
LiveBench reasoning89.2%77.6%Claude Opus 4.8
MMMU Pro (Vals AI)86.6%86.0%Claude Opus 4.8
GPQA Diamond (Artificial Analysis run)92.0%91.2%Claude Opus 4.8
Humanity's Last Exam (Artificial Analysis run)48.7%39.9%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%90.2%Claude Opus 4.8
ARC-AGI92.5%91.0%Claude Opus 4.8
ARC-AGI-272.1%65.8%Claude Opus 4.8
SimpleBench64.8%Not measuredOnly Claude Opus 4.8 measured
Chess puzzles52.0%21.0%Claude Opus 4.8
Mystery game puzzles36.0%8.0%Claude Opus 4.8
EBR-bench28.6%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: hard prompts14821490GLM 5.3 Flash
LMArena Text: expert15031511GLM 5.3 Flash
LMArena Text: hard prompts in English14871488GLM 5.3 Flash
LMArena Vision: diagrams13151317GLM 5.3 Flash
LMArena Vision: homework13371318Claude Opus 4.8
Kagi LLM Benchmark88.8%Not measuredOnly Claude Opus 4.8 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 Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
OTIS Mock AIME98.3%93.9%Claude Opus 4.8
FrontierMath, tiers 1 to 380.0%55.8%Claude Opus 4.8
FrontierMath, tier 456.1%17.1%Claude Opus 4.8
ProofBench69.0%21.0%Claude Opus 4.8
LMArena Text: math14861503GLM 5.3 Flash
LMArena Text: mathematical work14971497Claude Opus 4.8
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index34
Knowledge benchmarks for Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
MMLU Pro89.6%86.1%Claude Opus 4.8
LegalBench (Vals AI)83.6%83.9%GLM 5.3 Flash
CorpFin (Vals AI)66.7%Not measuredOnly Claude Opus 4.8 measured
TaxEval (Vals AI)75.6%75.6%Claude Opus 4.8
MortgageTax (Vals AI)69.9%Not measuredOnly Claude Opus 4.8 measured
MedCode (Vals AI)53.2%Not measuredOnly Claude Opus 4.8 measured
SimpleQA Verified53.0%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: science14771484GLM 5.3 Flash
LMArena Text: medicine and healthcare14641475GLM 5.3 Flash
LMArena Text: legal and government14771473Claude Opus 4.8
LMArena Text: business and finance14581460GLM 5.3 Flash
FACTS Benchmark Suite53.5%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index27
Web design benchmarks for Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
Design Arena: websites12581272GLM 5.3 Flash
Design Arena: UI components12551316GLM 5.3 Flash
Design Arena: game dev12641278GLM 5.3 Flash
Design Arena: data viz12401262GLM 5.3 Flash
Design Arena: 3D12221316GLM 5.3 Flash
Design Arena: all code categories12551282GLM 5.3 Flash
Design Arena: SVG11951285GLM 5.3 Flash
Design Arena: ASCII art12771267Claude Opus 4.8
LiveBench design78.8%77.2%Claude Opus 4.8
GeneralLike-for-likePublic boards, shown as published, kept out of the index1215
General benchmarks for Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
Vals IndexNot measured50.9%Only GLM 5.3 Flash measured
LiveBench data analysis66.0%76.4%GLM 5.3 Flash
Public Benefits Bench (Vals AI)68.1%Not measuredOnly Claude Opus 4.8 measured
SAGE (Vals AI)54.8%Not measuredOnly Claude Opus 4.8 measured
MedScribe (Vals AI)85.8%88.9%GLM 5.3 Flash
Vals Multimodal Index70.9%Not measuredOnly Claude Opus 4.8 measured
IFBench62.2%Not measuredOnly Claude Opus 4.8 measured
Long context reasoning (AA-LCR)77.7%80.0%GLM 5.3 Flash
DTBench94.9%Not measuredOnly Claude Opus 4.8 measured
LMCA57.5%Not measuredOnly Claude Opus 4.8 measured
Surface Evolver Bench87.5%52.5%Claude Opus 4.8
Furniture assembly42.5%Not measuredOnly Claude Opus 4.8 measured
LMArena Text14611471GLM 5.3 Flash
LMArena Text: instruction following14761478GLM 5.3 Flash
LMArena Text: creative writing14541441Claude Opus 4.8
LMArena Vision12941294Claude Opus 4.8
LMArena Text: English14681474GLM 5.3 Flash
LMArena Text: non-English14501462GLM 5.3 Flash
LMArena Text: Chinese15061531GLM 5.3 Flash
LMArena Text: German14721462Claude Opus 4.8
LMArena Text: Japanese14421444GLM 5.3 Flash
LMArena Text: Korean14311436GLM 5.3 Flash
LMArena Text: French14811491GLM 5.3 Flash
LMArena Text: Spanish14651475GLM 5.3 Flash
LMArena Text: Russian14741465Claude Opus 4.8
LMArena Text: Polish14591450Claude Opus 4.8
LMArena Text: multi-turn14761469Claude Opus 4.8
LMArena Text: longer queries14831481Claude Opus 4.8
LMArena Text: writing and language14611455Claude Opus 4.8
LMArena Text: entertainment and media14401440GLM 5.3 Flash
LMArena Vision: English12931295GLM 5.3 Flash
LMArena Vision: Chinese13461363GLM 5.3 Flash
LMArena Vision: reading text13031299Claude Opus 4.8
LMArena Vision: humor12821279Claude Opus 4.8
LMArena Vision: creative writing13011270Claude Opus 4.8
LMArena Document1475Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 10 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.8 and GLM 5.3 Flash
BenchmarkClaude Opus 4.8GLM 5.3 FlashLeader
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 4.8$0.018Fits in one request
GLM 5.3 Flash$0.0004Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.8$0.325Fits in one request
GLM 5.3 Flash$0.0090Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.8$1.25Fits in one request
GLM 5.3 Flash$0.035Fits in one request

GLM 5.3 Flash 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 4.8 and GLM 5.3 Flash
SpecificationAnthropic Claude Opus 4.8Z.ai GLM 5.3 Flash
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedMay 27, 2026August 26, 2026
Context window1M1.05M
Input $/Mtok$5.00$0.15
Output $/Mtok$25.00$0.50
Coding index65.057.7
Independent measurements behind it66
Cost per solved task$2.17$0.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than GLM 5.3 Flash for coding?

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 57.7 for GLM 5.3 Flash. Pick GLM 5.3 Flash for output tokens 50.0x cheaper ($0.50 vs $25.00 per million) and a lower cost per solved task ($0.02 against $2.17).

Which is cheaper, Claude Opus 4.8 or GLM 5.3 Flash?

Claude Opus 4.8 costs $5.00 per million input tokens and $25.00 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, Claude Opus 4.8 costs $2.17 and GLM 5.3 Flash $0.02.

Which has the bigger context window, Claude Opus 4.8 or GLM 5.3 Flash?

GLM 5.3 Flash, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 4.8 vs GLM 5.3 Flash comparison based on?

93 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.8's coding index rests on 6 independent benchmarks and GLM 5.3 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.

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