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Claude Opus 4.6 vs GLM 5.3 Flash

Updated October 21, 2026. 73 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Claude Opus 4.6 Replace GLM 5.3 Flash
Claude Opus 4.6Anthropic
Coding
66.9
Overall
31.9
Output $/M
$25.00
54
GLM 5.3 FlashZ.ai
Coding
71.0
Overall
41.8
Output $/M
$0.50
17
vs boards won of 73 shared, 2 tied

Decision reading

Pick GLM 5.3 Flash for coding: it scores 71.0 on the Vibe Coding Index against 66.9 for Claude Opus 4.6.

Pick Claude Opus 4.6 when what matters is LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads.

Model AClaude Opus 4.6Anthropic66.9/1002 independent benchmarks$1.56 per solved taskModel BGLM 5.3 FlashZ.ai71.0/1002 independent benchmarks$0.02 per solved task
Shared results
73
Claude Opus 4.6 only
35
GLM 5.3 Flash only
29
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 4.6 66.9 from 2 benchmarks, GLM 5.3 Flash 71.0 from 2 benchmarks.
Widest category
Math, 9.5 points apart on average over 6 shared benchmarks.
Widest single gap
ProofBench: Claude Opus 4.6 50.0% against GLM 5.3 Flash 21.0%, 29.0 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.6 $25.00 against GLM 5.3 Flash $0.50 per million output tokens, 50.0x apart.
Context window
Claude Opus 4.6 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 4.6BarsGLM 5.3 FlashTies
Coding46
Intelligence11
Agentic work01
Reasoning1022 ties
Math60
Knowledge70
Web design35
General232
All shared boards54172 ties
CodingLike-for-likeFour of these boards feed the Vibe Coding Index46
Coding benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 5.3 FlashLeader
SWE-bench Verified75.6%Not measuredOnly Claude Opus 4.6 measured
SWE-bench Multilingual72.0%Not measuredOnly Claude Opus 4.6 measured
LiveBench codingNot measured80.6%Only GLM 5.3 Flash measured
LMArena WebDev15471607GLM 5.3 Flash
AA Coding IndexNot measured71.5Only GLM 5.3 Flash measured
LiveCodeBench (Vals AI)84.7%80.5%Claude Opus 4.6
SWE-bench Verified (Vals AI)78.2%92.0%GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)Not measured37.4%Only GLM 5.3 Flash measured
Vibe Code Bench (Vals AI)57.6%30.8%Claude Opus 4.6
Code migration (Vals AI)Not measured20.5%Only GLM 5.3 Flash measured
ProgramBench (Vals AI)Not measured0.0%Only GLM 5.3 Flash measured
IOI (Vals AI)Not measured52.5%Only GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)Not measured62.9%Only GLM 5.3 Flash measured
Vibe Code Bench 1-100 (Vals AI)Not measured16.0%Only GLM 5.3 Flash measured
SkillsBench (Vals AI)Not measured40.2%Only GLM 5.3 Flash measured
CyberBench (Vals AI)Not measured67.9%Only GLM 5.3 Flash measured
SciCodeNot measured51.6%Only GLM 5.3 Flash measured
Terminal-Bench Hard (Artificial Analysis run)48.5%Not measuredOnly Claude Opus 4.6 measured
Terminal-Bench79.8%Not measuredOnly Claude Opus 4.6 measured
FrontierCode26.6%31.8%GLM 5.3 Flash
FrontierSWENot measured18.1%Only GLM 5.3 Flash measured
GSO-Bench41.2%Not measuredOnly Claude Opus 4.6 measured
WeirdML78.0%Not measuredOnly Claude Opus 4.6 measured
Cybench93.0%Not measuredOnly Claude Opus 4.6 measured
ALE-BenchNot measured303.6Only GLM 5.3 Flash measured
LMArena Text: coding15341507Claude Opus 4.6
LMArena Text: software and IT15271500Claude Opus 4.6
LMArena WebDev: React15391624GLM 5.3 Flash
LMArena WebDev: HTML15591577GLM 5.3 Flash
LMArena WebDev: from an image15431578GLM 5.3 Flash
Neither model has a result on the other 8 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 5.3 FlashLeader
AA Intelligence Index31.941.8GLM 5.3 Flash
Epoch Capabilities Index155.7153.1Claude Opus 4.6
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 5.3 FlashLeader
AA Agentic IndexNot measured50.9Only GLM 5.3 Flash measured
Design Arena: agents building web apps1206Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building full-stack apps1220Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building mobile apps1207Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building Android apps1204Not measuredOnly Claude Opus 4.6 measured
Design Arena: agents building games1214Not measuredOnly Claude Opus 4.6 measured
LiveBench researchNot measured70.1%Only GLM 5.3 Flash measured
LiveBench browserNot measured84.0%Only GLM 5.3 Flash measured
LiveBench long agenticNot measured28.4%Only GLM 5.3 Flash measured
SREBench (Vals AI)Not measured0.8%Only GLM 5.3 Flash measured
Finance Agent (Vals AI)Not measured57.9%Only GLM 5.3 Flash measured
Tax Agent Bench (Vals AI)Not measured31.6%Only GLM 5.3 Flash measured
Legal Research Bench (Vals AI)Not measured45.2%Only GLM 5.3 Flash measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured10.4%Only GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)Not measured55.9%Only GLM 5.3 Flash measured
Terminal-Bench-Science (Vals AI)Not measured2.9%Only GLM 5.3 Flash measured
τ²-Bench Telecom92.1%Not measuredOnly Claude Opus 4.6 measured
APEX-Agents46.3%52.8%GLM 5.3 Flash
METR time horizons78.9%Not measuredOnly Claude Opus 4.6 measured
Remote Labor Index4.2%Not measuredOnly Claude Opus 4.6 measured
DeepResearch Bench55.3%Not measuredOnly Claude Opus 4.6 measured
Vending-Bench 2$8,018Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 17 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index102
Reasoning benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 5.3 FlashLeader
GPQA Diamond89.7%86.4%Claude Opus 4.6
LiveBench reasoningNot measured77.6%Only GLM 5.3 Flash measured
MMMU Pro (Vals AI)83.9%86.0%GLM 5.3 Flash
GPQA Diamond (Artificial Analysis run)89.6%91.2%GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)39.9%39.9%Tie
GPQA Diamond (Epoch AI run)90.5%90.2%Claude Opus 4.6
ARC-AGI94.0%91.0%Claude Opus 4.6
ARC-AGI-269.2%65.8%Claude Opus 4.6
SimpleBench67.6%Not measuredOnly Claude Opus 4.6 measured
Chess puzzles21.0%21.0%Tie
Mystery game puzzles25.0%8.0%Claude Opus 4.6
EBR-bench12.7%Not measuredOnly Claude Opus 4.6 measured
LMArena Text: hard prompts15251490Claude Opus 4.6
LMArena Text: expert15441511Claude Opus 4.6
LMArena Text: hard prompts in English15301488Claude Opus 4.6
LMArena Vision: diagrams13401317Claude Opus 4.6
LMArena Vision: homework13371318Claude Opus 4.6
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 5.3 FlashLeader
AIME95.6%Not measuredOnly Claude Opus 4.6 measured
OTIS Mock AIME94.4%93.9%Claude Opus 4.6
FrontierMath, tiers 1 to 366.0%55.8%Claude Opus 4.6
FrontierMath, tier 426.8%17.1%Claude Opus 4.6
ProofBench50.0%21.0%Claude Opus 4.6
LMArena Text: math15181503Claude Opus 4.6
LMArena Text: mathematical work15251497Claude Opus 4.6
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index70
Knowledge benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 5.3 FlashLeader
MMLU Pro89.1%86.1%Claude Opus 4.6
LegalBench (Vals AI)85.3%83.9%Claude Opus 4.6
CaseLaw (Vals AI)62.1%Not measuredOnly Claude Opus 4.6 measured
CorpFin (Vals AI)67.0%Not measuredOnly Claude Opus 4.6 measured
TaxEval (Vals AI)76.0%75.6%Claude Opus 4.6
MortgageTax (Vals AI)68.5%Not measuredOnly Claude Opus 4.6 measured
MedQA (Vals AI)95.4%Not measuredOnly Claude Opus 4.6 measured
MedCode (Vals AI)49.1%Not measuredOnly Claude Opus 4.6 measured
SimpleQA Verified47.0%Not measuredOnly Claude Opus 4.6 measured
LMArena Text: science15191484Claude Opus 4.6
LMArena Text: medicine and healthcare15041475Claude Opus 4.6
LMArena Text: legal and government15121473Claude Opus 4.6
LMArena Text: business and finance14971460Claude Opus 4.6
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index35
Web design benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 5.3 FlashLeader
Design Arena: websites12911272Claude Opus 4.6
Design Arena: UI components12841316GLM 5.3 Flash
Design Arena: game dev12781279GLM 5.3 Flash
Design Arena: data viz12791262Claude Opus 4.6
Design Arena: 3D12741316GLM 5.3 Flash
Design Arena: all code categories12891282Claude Opus 4.6
Design Arena: SVG12271284GLM 5.3 Flash
Design Arena: ASCII art12541269GLM 5.3 Flash
LiveBench designNot measured77.2%Only GLM 5.3 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index232
General benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 5.3 FlashLeader
Vals IndexNot measured50.9%Only GLM 5.3 Flash measured
LiveBench data analysisNot measured76.4%Only GLM 5.3 Flash measured
SAGE (Vals AI)51.6%Not measuredOnly Claude Opus 4.6 measured
MedScribe (Vals AI)86.7%88.9%GLM 5.3 Flash
IFBench53.1%Not measuredOnly Claude Opus 4.6 measured
Long context reasoning (AA-LCR)78.0%80.0%GLM 5.3 Flash
DTBench91.2%Not measuredOnly Claude Opus 4.6 measured
LMCA55.8%Not measuredOnly Claude Opus 4.6 measured
CL-bench20.7%Not measuredOnly Claude Opus 4.6 measured
Surface Evolver BenchNot measured52.5%Only GLM 5.3 Flash measured
Furniture assembly28.3%Not measuredOnly Claude Opus 4.6 measured
CL-bench Life17.0%Not measuredOnly Claude Opus 4.6 measured
LMArena Text15011471Claude Opus 4.6
LMArena Text: instruction following15211478Claude Opus 4.6
LMArena Text: creative writing15051441Claude Opus 4.6
LMArena Vision13161294Claude Opus 4.6
LMArena Text: English15111474Claude Opus 4.6
LMArena Text: non-English14881462Claude Opus 4.6
LMArena Text: Chinese15511531Claude Opus 4.6
LMArena Text: German15001462Claude Opus 4.6
LMArena Text: Japanese14881444Claude Opus 4.6
LMArena Text: Korean14641436Claude Opus 4.6
LMArena Text: French15121491Claude Opus 4.6
LMArena Text: Spanish15101475Claude Opus 4.6
LMArena Text: Russian14971465Claude Opus 4.6
LMArena Text: Polish14991450Claude Opus 4.6
LMArena Text: multi-turn15111469Claude Opus 4.6
LMArena Text: longer queries15181481Claude Opus 4.6
LMArena Text: writing and language15021455Claude Opus 4.6
LMArena Text: entertainment and media14921440Claude Opus 4.6
LMArena Vision: English13241295Claude Opus 4.6
LMArena Vision: Chinese13701363Claude Opus 4.6
LMArena Vision: reading text13261299Claude Opus 4.6
LMArena Vision: humor13141279Claude Opus 4.6
LMArena Vision: recognizing things1274Not measuredOnly Claude Opus 4.6 measured
LMArena Vision: creative writing13311270Claude Opus 4.6
LMArena Document1507Not measuredOnly Claude Opus 4.6 measured
Neither model has a result on the other 9 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.6 and GLM 5.3 Flash
BenchmarkClaude Opus 4.6GLM 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 4.6$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 4.6$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 4.6$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 4.6 and GLM 5.3 Flash
SpecificationAnthropic Claude Opus 4.6Z.ai GLM 5.3 Flash
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedFebruary 4, 2026August 26, 2026
Context window1M1.05M
Input $/Mtok$5.00$0.15
Output $/Mtok$25.00$0.50
Coding index66.971.0
Independent measurements behind it22
Cost per solved task$1.56$0.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.6 better than GLM 5.3 Flash for coding?

Pick GLM 5.3 Flash for coding: it scores 71.0 on the Vibe Coding Index against 66.9 for Claude Opus 4.6. Pick Claude Opus 4.6 when what matters is LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads.

Which is cheaper, Claude Opus 4.6 or GLM 5.3 Flash?

Claude Opus 4.6 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 4.6 costs $1.56 and GLM 5.3 Flash $0.02.

Which has the bigger context window, Claude Opus 4.6 or GLM 5.3 Flash?

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

How many benchmarks is the Claude Opus 4.6 vs GLM 5.3 Flash comparison based on?

73 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.6's coding index rests on 2 independent benchmarks and GLM 5.3 Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

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