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Claude Sonnet 4.6 vs GLM 5.3 Flash

GLM 5.3 Flash leads Claude Sonnet 4.6 on coding, 57.7 to 57.3 on the Vibe Coding Index, and GLM 5.3 Flash costs 30.0x less per output token ($0.50 vs $15.00 per million). Updated October 21, 2026; 88 benchmarks have a result for both.

Replace Claude Sonnet 4.6 Replace GLM 5.3 Flash
Claude Sonnet 4.6Anthropic
Coding
57.3
Overall
60.3
Output $/M
$15.00
18
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
69
vs boards won of 88 shared, 1 tied

Claude Sonnet 4.6 or GLM 5.3 Flash: which to pick

Claude Sonnet 4.6 and GLM 5.3 Flash are level for coding, 57.3 against 57.7 on the Vibe Coding Index, so price and context decide.

Pick Claude Sonnet 4.6 for work measured by LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads. Pick GLM 5.3 Flash for output tokens 30.0x cheaper ($0.50 vs $15.00 per million) and a lower cost per solved task ($0.02 against $1.68).

Model AClaude Sonnet 4.6Anthropic57.3/1005 independent benchmarks$1.68 per solved taskModel BGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved task
Shared results
88
Claude Sonnet 4.6 only
30
GLM 5.3 Flash only
14
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 Sonnet 4.6 57.3 from 5 benchmarks, GLM 5.3 Flash 57.7 from 6 benchmarks.
Widest category
Math, 10.3 points apart on average over 4 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Claude Sonnet 4.6 55.8% against GLM 5.3 Flash 30.8%, 25.0 points apart on a 0 to 100 scale.
Output price
Claude Sonnet 4.6 $15.00 against GLM 5.3 Flash $0.50 per million output tokens, 30.0x apart.
Context window
Claude Sonnet 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 Sonnet 4.6BarsGLM 5.3 FlashTies
Coding512
Intelligence02
Agentic work18
Reasoning411
Math13
Knowledge34
Web design27
General2221 tie
All shared boards18691 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index512
Coding benchmarks for Claude Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 4.6GLM 5.3 FlashLeader
LiveBench coding66.6%80.6%GLM 5.3 Flash
LMArena WebDev15231607GLM 5.3 Flash
AA Coding Index63.071.5GLM 5.3 Flash
LiveCodeBench (Vals AI)82.1%80.5%Claude Sonnet 4.6
SWE-bench Verified (Vals AI)77.4%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)55.8%30.8%Claude Sonnet 4.6
Code migration (Vals AI)39.9%20.5%Claude Sonnet 4.6
ProgramBench (Vals AI)0.5%0.0%Claude Sonnet 4.6
IOI (Vals AI)Not measured52.5%Only GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)57.3%62.9%GLM 5.3 Flash
Vibe Code Bench 1-100 (Vals AI)Not measured16.0%Only GLM 5.3 Flash measured
SkillsBench (Vals AI)49.0%40.2%Claude Sonnet 4.6
CyberBench (Vals AI)Not measured67.9%Only GLM 5.3 Flash measured
SciCode50.1%51.6%GLM 5.3 Flash
Terminal-Bench Hard (Artificial Analysis run)53.0%Not measuredOnly Claude Sonnet 4.6 measured
Terminal-Bench53.4%Not measuredOnly Claude Sonnet 4.6 measured
FrontierCode24.3%31.8%GLM 5.3 Flash
FrontierSWENot measured18.1%Only GLM 5.3 Flash measured
WeirdML66.1%Not measuredOnly Claude Sonnet 4.6 measured
ALE-BenchNot measured303.6Only GLM 5.3 Flash measured
LMArena Text: coding15031507GLM 5.3 Flash
LMArena Text: software and IT14911500GLM 5.3 Flash
LMArena WebDev: React15121624GLM 5.3 Flash
LMArena WebDev: HTML15271577GLM 5.3 Flash
LMArena WebDev: from an image15291578GLM 5.3 Flash
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Claude Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 4.6GLM 5.3 FlashLeader
AA Intelligence Index30.141.8GLM 5.3 Flash
Epoch Capabilities Index152.8153.1GLM 5.3 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index18
Agentic work benchmarks for Claude Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 4.6GLM 5.3 FlashLeader
AA Agentic Index31.850.9GLM 5.3 Flash
Design Arena: agents building web apps1190Not measuredOnly Claude Sonnet 4.6 measured
Design Arena: agents building full-stack apps1213Not measuredOnly Claude Sonnet 4.6 measured
Design Arena: agents building mobile apps1212Not measuredOnly Claude Sonnet 4.6 measured
Design Arena: agents building Android apps1196Not measuredOnly Claude Sonnet 4.6 measured
Design Arena: agents building Godot games1226Not measuredOnly Claude Sonnet 4.6 measured
Design Arena: agents building games1177Not measuredOnly Claude Sonnet 4.6 measured
LiveBench research63.6%70.1%GLM 5.3 Flash
LiveBench browser68.0%84.0%GLM 5.3 Flash
LiveBench long agentic23.1%28.4%GLM 5.3 Flash
SREBench (Vals AI)Not measured0.8%Only GLM 5.3 Flash measured
Finance Agent (Vals AI)51.0%57.9%GLM 5.3 Flash
Tax Agent Bench (Vals AI)25.8%31.6%GLM 5.3 Flash
Legal Research Bench (Vals AI)38.5%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)60.2%55.9%Claude Sonnet 4.6
Terminal-Bench-Science (Vals AI)Not measured2.9%Only GLM 5.3 Flash measured
τ²-Bench Telecom79.5%Not measuredOnly Claude Sonnet 4.6 measured
APEX-Agents43.0%52.8%GLM 5.3 Flash
OSWorld 2.09.3%Not measuredOnly Claude Sonnet 4.6 measured
DeepResearch Bench54.9%Not measuredOnly Claude Sonnet 4.6 measured
OSWorld72.1%Not measuredOnly Claude Sonnet 4.6 measured
Vending-Bench 2$7,204Not measuredOnly Claude Sonnet 4.6 measured
Neither model has a result on the other 18 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index411
Reasoning benchmarks for Claude Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 4.6GLM 5.3 FlashLeader
GPQA Diamond85.6%86.4%GLM 5.3 Flash
LiveBench reasoning86.4%77.6%Claude Sonnet 4.6
MMMU Pro (Vals AI)83.6%86.0%GLM 5.3 Flash
GPQA Diamond (Artificial Analysis run)87.5%91.2%GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)33.6%39.9%GLM 5.3 Flash
GPQA Diamond (Epoch AI run)87.4%90.2%GLM 5.3 Flash
ARC-AGI86.5%91.0%GLM 5.3 Flash
ARC-AGI-260.4%65.8%GLM 5.3 Flash
Chess puzzles23.0%21.0%Claude Sonnet 4.6
Mystery game puzzles16.0%8.0%Claude Sonnet 4.6
LMArena Text: hard prompts14851490GLM 5.3 Flash
LMArena Text: expert15001511GLM 5.3 Flash
LMArena Text: hard prompts in English14931488Claude Sonnet 4.6
LMArena Vision: diagrams13061317GLM 5.3 Flash
LMArena Vision: homework13111318GLM 5.3 Flash
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index13
Math benchmarks for Claude Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 4.6GLM 5.3 FlashLeader
AIME92.3%Not measuredOnly Claude Sonnet 4.6 measured
OTIS Mock AIME85.8%93.9%GLM 5.3 Flash
FrontierMath, tiers 1 to 3Not measured55.8%Only GLM 5.3 Flash measured
FrontierMath, tier 4Not measured17.1%Only GLM 5.3 Flash measured
ProofBench45.0%21.0%Claude Sonnet 4.6
LMArena Text: math14621503GLM 5.3 Flash
LMArena Text: mathematical work14831497GLM 5.3 Flash
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index34
Knowledge benchmarks for Claude Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 4.6GLM 5.3 FlashLeader
MMLU Pro87.3%86.1%Claude Sonnet 4.6
LegalBench (Vals AI)82.1%83.9%GLM 5.3 Flash
CaseLaw (Vals AI)64.0%Not measuredOnly Claude Sonnet 4.6 measured
CorpFin (Vals AI)65.3%Not measuredOnly Claude Sonnet 4.6 measured
TaxEval (Vals AI)77.1%75.6%Claude Sonnet 4.6
MortgageTax (Vals AI)67.7%Not measuredOnly Claude Sonnet 4.6 measured
MedQA (Vals AI)92.1%Not measuredOnly Claude Sonnet 4.6 measured
SimpleQA Verified35.5%Not measuredOnly Claude Sonnet 4.6 measured
LMArena Text: science14741484GLM 5.3 Flash
LMArena Text: medicine and healthcare14511475GLM 5.3 Flash
LMArena Text: legal and government14701473GLM 5.3 Flash
LMArena Text: business and finance14641460Claude Sonnet 4.6
FACTS Benchmark Suite37.0%Not measuredOnly Claude Sonnet 4.6 measured
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index27
Web design benchmarks for Claude Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 4.6GLM 5.3 FlashLeader
Design Arena: websites12851272Claude Sonnet 4.6
Design Arena: UI components12721316GLM 5.3 Flash
Design Arena: game dev12591278GLM 5.3 Flash
Design Arena: data viz12771261Claude Sonnet 4.6
Design Arena: 3D12341316GLM 5.3 Flash
Design Arena: all code categories12761282GLM 5.3 Flash
Design Arena: SVG11971284GLM 5.3 Flash
Design Arena: ASCII art12351268GLM 5.3 Flash
LiveBench design71.8%77.2%GLM 5.3 Flash
GeneralLike-for-likePublic boards, shown as published, kept out of the index222
General benchmarks for Claude Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 4.6GLM 5.3 FlashLeader
Vals IndexNot measured50.9%Only GLM 5.3 Flash measured
LiveBench data analysis76.1%76.4%GLM 5.3 Flash
Public Benefits Bench (Vals AI)62.5%Not measuredOnly Claude Sonnet 4.6 measured
SAGE (Vals AI)46.6%Not measuredOnly Claude Sonnet 4.6 measured
MedScribe (Vals AI)Not measured88.9%Only GLM 5.3 Flash measured
Vals Multimodal Index60.6%Not measuredOnly Claude Sonnet 4.6 measured
IFBench56.6%Not measuredOnly Claude Sonnet 4.6 measured
Long context reasoning (AA-LCR)80.0%80.0%Tie
DTBench89.9%Not measuredOnly Claude Sonnet 4.6 measured
LMCA46.5%Not measuredOnly Claude Sonnet 4.6 measured
Surface Evolver BenchNot measured52.5%Only GLM 5.3 Flash measured
ExploitBench23.6%Not measuredOnly Claude Sonnet 4.6 measured
LMArena Text14581471GLM 5.3 Flash
LMArena Text: instruction following14761478GLM 5.3 Flash
LMArena Text: creative writing14351441GLM 5.3 Flash
LMArena Vision12831294GLM 5.3 Flash
LMArena Text: English14721474GLM 5.3 Flash
LMArena Text: non-English14401462GLM 5.3 Flash
LMArena Text: Chinese14911531GLM 5.3 Flash
LMArena Text: German14281462GLM 5.3 Flash
LMArena Text: Japanese14201444GLM 5.3 Flash
LMArena Text: Korean14101436GLM 5.3 Flash
LMArena Text: French14651491GLM 5.3 Flash
LMArena Text: Spanish14641475GLM 5.3 Flash
LMArena Text: Russian14401465GLM 5.3 Flash
LMArena Text: Polish14431450GLM 5.3 Flash
LMArena Text: multi-turn14641469GLM 5.3 Flash
LMArena Text: longer queries14791481GLM 5.3 Flash
LMArena Text: writing and language14441455GLM 5.3 Flash
LMArena Text: entertainment and media14311440GLM 5.3 Flash
LMArena Vision: English12981295Claude Sonnet 4.6
LMArena Vision: Chinese13071363GLM 5.3 Flash
LMArena Vision: reading text12961299GLM 5.3 Flash
LMArena Vision: humor12481279GLM 5.3 Flash
LMArena Vision: recognizing things1195Not measuredOnly Claude Sonnet 4.6 measured
LMArena Vision: creative writing12721270Claude Sonnet 4.6
LMArena Document1482Not measuredOnly Claude Sonnet 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 Sonnet 4.6 and GLM 5.3 Flash
BenchmarkClaude Sonnet 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 Sonnet 4.6$0.011Fits 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 Sonnet 4.6$0.195Fits 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 Sonnet 4.6$0.750Fits 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 Sonnet 4.6 and GLM 5.3 Flash
SpecificationAnthropic Claude Sonnet 4.6Z.ai GLM 5.3 Flash
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedFebruary 17, 2026August 26, 2026
Context window1M1.05M
Input $/Mtok$3.00$0.15
Output $/Mtok$15.00$0.50
Coding index57.357.7
Independent measurements behind it56
Cost per solved task$1.68$0.02
SourceOpenRouter listingOpenRouter listing

Questions

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

Claude Sonnet 4.6 and GLM 5.3 Flash are level for coding, 57.3 against 57.7 on the Vibe Coding Index, so price and context decide. Pick Claude Sonnet 4.6 for work measured by LiveCodeBench (Vals AI) or Vibe Code Bench (Vals AI), where it leads. Pick GLM 5.3 Flash for output tokens 30.0x cheaper ($0.50 vs $15.00 per million) and a lower cost per solved task ($0.02 against $1.68).

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

Claude Sonnet 4.6 costs $3.00 per million input tokens and $15.00 per million output tokens; GLM 5.3 Flash costs $0.15 and $0.50. Per solved SWE-bench Verified task, Claude Sonnet 4.6 costs $1.68 and GLM 5.3 Flash $0.02.

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

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

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

88 benchmarks have a result for both models as of October 21, 2026. Claude Sonnet 4.6's coding index rests on 5 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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