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Claude Sonnet 4.6 vs GLM 5.2

GLM 5.2 leads Claude Sonnet 4.6 on coding, 61.1 to 57.3 on the Vibe Coding Index, and GLM 5.2 costs 3.4x less per output token ($4.40 vs $15.00 per million). Updated October 21, 2026; 85 benchmarks have a result for both.

Replace Claude Sonnet 4.6 Replace GLM 5.2
Claude Sonnet 4.6Anthropic
Coding
57.3
Overall
60.3
Output $/M
$15.00
27
GLM 5.2Z.ai
Coding
61.1
Overall
62.5
Output $/M
$4.40
55
vs boards won of 85 shared, 3 tied

Claude Sonnet 4.6 or GLM 5.2: which to pick

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 57.3 for Claude Sonnet 4.6, though on 4 benchmarks against 5.

Pick Claude Sonnet 4.6 for work measured by LiveCodeBench (Vals AI) or Code migration (Vals AI), where it leads.

Model AClaude Sonnet 4.6Anthropic57.3/1005 independent benchmarks$1.68 per solved taskModel BGLM 5.2Z.ai61.1/1004 independent benchmarks$0.86 per solved task
Shared results
85
Claude Sonnet 4.6 only
33
GLM 5.2 only
13
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 5.2 61.1 from 4 benchmarks.
Widest category
Reasoning, 6.4 points apart on average over 11 shared benchmarks.
Widest single gap
ARC-AGI-2: Claude Sonnet 4.6 60.4% against GLM 5.2 22.8%, 37.6 points apart on a 0 to 100 scale.
Output price
Claude Sonnet 4.6 $15.00 against GLM 5.2 $4.40 per million output tokens, 3.4x apart.
Context window
Claude Sonnet 4.6 takes 1M tokens, GLM 5.2 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 5.2Ties
Coding6101 tie
Intelligence11
Agentic work58
Reasoning641 tie
Math13
Knowledge45
Web design161 tie
General318
All shared boards27553 ties
CodingLike-for-likeSix of these boards feed the Vibe Coding Index610
Coding benchmarks for Claude Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
LiveBench coding66.6%Not measuredOnly Claude Sonnet 4.6 measured
LMArena WebDev15231604GLM 5.2
AA Coding Index63.068.8GLM 5.2
LiveCodeBench (Vals AI)82.1%69.5%Claude Sonnet 4.6
SWE-bench Verified (Vals AI)77.4%82.8%GLM 5.2
Vibe Code Bench (Vals AI)55.8%64.0%GLM 5.2
Code migration (Vals AI)39.9%37.9%Claude Sonnet 4.6
ProgramBench (Vals AI)0.5%0.5%Tie
Terminal-Bench 2.1 (Vals AI)57.3%67.8%GLM 5.2
SkillsBench (Vals AI)49.0%45.1%Claude Sonnet 4.6
SciCode50.1%51.2%GLM 5.2
Terminal-Bench Hard (Artificial Analysis run)53.0%50.8%Claude Sonnet 4.6
Terminal-Bench53.4%Not measuredOnly Claude Sonnet 4.6 measured
FrontierCode24.3%24.5%GLM 5.2
WeirdML66.1%70.1%GLM 5.2
ALE-BenchNot measured1047.0Only GLM 5.2 measured
LMArena Text: coding15031487Claude Sonnet 4.6
LMArena Text: software and IT14911486Claude Sonnet 4.6
LMArena WebDev: React15121617GLM 5.2
LMArena WebDev: HTML15271565GLM 5.2
LMArena WebDev: from an image1529Not measuredOnly Claude Sonnet 4.6 measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Claude Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
AA Intelligence Index30.133.7GLM 5.2
Epoch Capabilities Index152.8151.9Claude Sonnet 4.6
Agentic workLike-for-likePublic boards, shown as published, kept out of the index58
Agentic work benchmarks for Claude Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
AA Agentic Index31.838.4GLM 5.2
Design Arena: agents building web apps11901222GLM 5.2
Design Arena: agents building full-stack apps12131241GLM 5.2
Design Arena: agents building mobile apps12121160Claude Sonnet 4.6
Design Arena: agents building Android apps11961178Claude Sonnet 4.6
Design Arena: agents building Godot games12261142Claude Sonnet 4.6
Design Arena: agents building games11771206GLM 5.2
Design Arena: HTML slidesNot measured1175Only GLM 5.2 measured
Design Arena: PowerPoint slidesNot measured1195Only GLM 5.2 measured
LiveBench research63.6%Not measuredOnly Claude Sonnet 4.6 measured
LiveBench browser68.0%Not measuredOnly Claude Sonnet 4.6 measured
LiveBench long agentic23.1%Not measuredOnly Claude Sonnet 4.6 measured
SREBench (Vals AI)Not measured0.0%Only GLM 5.2 measured
Finance Agent (Vals AI)51.0%49.7%Claude Sonnet 4.6
Tax Agent Bench (Vals AI)25.8%Not measuredOnly Claude Sonnet 4.6 measured
Legal Research Bench (Vals AI)38.5%31.3%Claude Sonnet 4.6
Excel Modeling Benchmark (Vals AI)60.2%61.5%GLM 5.2
τ²-Bench Telecom79.5%99.1%GLM 5.2
APEX-Agents43.0%45.2%GLM 5.2
OSWorld 2.09.3%Not measuredOnly Claude Sonnet 4.6 measured
DeepResearch Bench54.9%Not measuredOnly Claude Sonnet 4.6 measured
PostTrainBenchNot measured31.7%Only GLM 5.2 measured
OSWorld72.1%Not measuredOnly Claude Sonnet 4.6 measured
Vending-Bench 2$7,204$8,314GLM 5.2
Neither model has a result on the other 17 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index64
Reasoning benchmarks for Claude Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
GPQA Diamond85.6%85.6%Tie
LiveBench reasoning86.4%Not measuredOnly Claude Sonnet 4.6 measured
MMMU Pro (Vals AI)83.6%Not measuredOnly Claude Sonnet 4.6 measured
GPQA Diamond (Artificial Analysis run)87.5%89.5%GLM 5.2
Humanity's Last Exam (Artificial Analysis run)33.6%41.1%GLM 5.2
GPQA Diamond (Epoch AI run)87.4%91.9%GLM 5.2
ARC-AGI86.5%77.0%Claude Sonnet 4.6
ARC-AGI-260.4%22.8%Claude Sonnet 4.6
SimpleBenchNot measured58.8%Only GLM 5.2 measured
Chess puzzles23.0%22.0%Claude Sonnet 4.6
Mystery game puzzles16.0%19.0%GLM 5.2
EBR-benchNot measured9.5%Only GLM 5.2 measured
LMArena Text: hard prompts14851481Claude Sonnet 4.6
LMArena Text: expert15001487Claude Sonnet 4.6
LMArena Text: hard prompts in English14931481Claude Sonnet 4.6
LMArena Vision: diagrams1306Not measuredOnly Claude Sonnet 4.6 measured
LMArena Vision: homework1311Not measuredOnly Claude Sonnet 4.6 measured
Kagi LLM BenchmarkNot measured62.6%Only GLM 5.2 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index13
Math benchmarks for Claude Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
AIME92.3%Not measuredOnly Claude Sonnet 4.6 measured
OTIS Mock AIME85.8%86.4%GLM 5.2
FrontierMath, tiers 1 to 3Not measured59.2%Only GLM 5.2 measured
FrontierMath, tier 4Not measured29.3%Only GLM 5.2 measured
ProofBench45.0%35.0%Claude Sonnet 4.6
LMArena Text: math14621483GLM 5.2
LMArena Text: mathematical work14831489GLM 5.2
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index45
Knowledge benchmarks for Claude Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
MMLU Pro87.3%86.7%Claude Sonnet 4.6
LegalBench (Vals AI)82.1%84.1%GLM 5.2
CaseLaw (Vals AI)64.0%Not measuredOnly Claude Sonnet 4.6 measured
CorpFin (Vals AI)65.3%66.1%GLM 5.2
TaxEval (Vals AI)77.1%73.3%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
MedCode (Vals AI)Not measured40.8%Only GLM 5.2 measured
SimpleQA Verified35.5%34.2%Claude Sonnet 4.6
LMArena Text: science14741489GLM 5.2
LMArena Text: medicine and healthcare14511475GLM 5.2
LMArena Text: legal and government14701486GLM 5.2
LMArena Text: business and finance14641451Claude Sonnet 4.6
FACTS Benchmark Suite37.0%Not measuredOnly Claude Sonnet 4.6 measured
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index16
Web design benchmarks for Claude Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
Design Arena: websites12851285Tie
Design Arena: UI components12721296GLM 5.2
Design Arena: game dev12591268GLM 5.2
Design Arena: data viz12771285GLM 5.2
Design Arena: 3D12341288GLM 5.2
Design Arena: all code categories12761288GLM 5.2
Design Arena: SVG11971214GLM 5.2
Design Arena: ASCII art12351190Claude Sonnet 4.6
LiveBench design71.8%Not measuredOnly Claude Sonnet 4.6 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index318
General benchmarks for Claude Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
LiveBench data analysis76.1%Not measuredOnly Claude Sonnet 4.6 measured
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 measured83.5%Only GLM 5.2 measured
Vals Multimodal Index60.6%Not measuredOnly Claude Sonnet 4.6 measured
IFBench56.6%73.3%GLM 5.2
Long context reasoning (AA-LCR)80.0%78.3%Claude Sonnet 4.6
DTBench89.9%93.6%GLM 5.2
LMCA46.5%45.8%Claude Sonnet 4.6
Surface Evolver BenchNot measured55.6%Only GLM 5.2 measured
ExploitBench23.6%Not measuredOnly Claude Sonnet 4.6 measured
LMArena Text14581470GLM 5.2
LMArena Text: instruction following14761466Claude Sonnet 4.6
LMArena Text: creative writing14351463GLM 5.2
LMArena Vision1283Not measuredOnly Claude Sonnet 4.6 measured
LMArena Text: English14721475GLM 5.2
LMArena Text: non-English14401459GLM 5.2
LMArena Text: Chinese14911522GLM 5.2
LMArena Text: German14281470GLM 5.2
LMArena Text: Japanese14201450GLM 5.2
LMArena Text: Korean14101440GLM 5.2
LMArena Text: French14651479GLM 5.2
LMArena Text: Spanish14641478GLM 5.2
LMArena Text: Russian14401468GLM 5.2
LMArena Text: Polish14431456GLM 5.2
LMArena Text: multi-turn14641469GLM 5.2
LMArena Text: longer queries14791480GLM 5.2
LMArena Text: writing and language14441463GLM 5.2
LMArena Text: entertainment and media14311450GLM 5.2
LMArena Vision: English1298Not measuredOnly Claude Sonnet 4.6 measured
LMArena Vision: Chinese1307Not measuredOnly Claude Sonnet 4.6 measured
LMArena Vision: reading text1296Not measuredOnly Claude Sonnet 4.6 measured
LMArena Vision: humor1248Not measuredOnly Claude Sonnet 4.6 measured
LMArena Vision: recognizing things1195Not measuredOnly Claude Sonnet 4.6 measured
LMArena Vision: creative writing1272Not measuredOnly Claude Sonnet 4.6 measured
LMArena Document1482Not measuredOnly Claude Sonnet 4.6 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 Sonnet 4.6 and GLM 5.2
BenchmarkClaude Sonnet 4.6GLM 5.2Leader
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 5.2$0.0036Fits in one request

GLM 5.2 costs less

Repository review

50K input + 3K output tokens

Claude Sonnet 4.6$0.195Fits in one request
GLM 5.2$0.083Fits in one request

GLM 5.2 costs less

Agent loop

200K input + 10K output tokens

Claude Sonnet 4.6$0.750Fits in one request
GLM 5.2$0.324Fits in one request

GLM 5.2 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 5.2
SpecificationAnthropic Claude Sonnet 4.6Z.ai GLM 5.2
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedFebruary 17, 2026June 16, 2026
Context window1M1.05M
Input $/Mtok$3.00$1.40
Output $/Mtok$15.00$4.40
Coding index57.361.1
Independent measurements behind it54
Cost per solved task$1.68$0.86
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Sonnet 4.6 better than GLM 5.2 for coding?

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 57.3 for Claude Sonnet 4.6, though on 4 benchmarks against 5. Pick Claude Sonnet 4.6 for work measured by LiveCodeBench (Vals AI) or Code migration (Vals AI), where it leads.

Which is cheaper, Claude Sonnet 4.6 or GLM 5.2?

Claude Sonnet 4.6 costs $3.00 per million input tokens and $15.00 per million output tokens; GLM 5.2 costs $1.40 and $4.40. Per solved SWE-bench Verified task, Claude Sonnet 4.6 costs $1.68 and GLM 5.2 $0.86.

Which has the bigger context window, Claude Sonnet 4.6 or GLM 5.2?

GLM 5.2, with 1.05M tokens against 1M.

How many benchmarks is the Claude Sonnet 4.6 vs GLM 5.2 comparison based on?

85 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 5.2's on 4. Where only one model has a result, the page says so instead of naming a winner.

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