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Claude Sonnet 4.6 vs GLM 4.7

Claude Sonnet 4.6 leads GLM 4.7 on coding, 57.3 to 55.1 on the Vibe Coding Index, and GLM 4.7 costs 6.8x less per output token ($2.20 vs $15.00 per million). Updated October 22, 2026; 69 benchmarks have a result for both.

Replace Claude Sonnet 4.6 Replace GLM 4.7
Claude Sonnet 4.6Anthropic
Coding
57.3
Overall
60.3
Output $/M
$15.00
60
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
9
vs boards won of 69 shared

Claude Sonnet 4.6 or GLM 4.7: which to pick

Pick Claude Sonnet 4.6 for coding: it scores 57.3 on the Vibe Coding Index against 55.1 for GLM 4.7.

Pick GLM 4.7 for output tokens 6.8x cheaper ($2.20 vs $15.00 per million) and a lower cost per solved task ($0.29 against $1.68).

Model AClaude Sonnet 4.6Anthropic57.3/1005 independent benchmarks$1.68 per solved taskModel BGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved task
Shared results
69
Claude Sonnet 4.6 only
49
GLM 4.7 only
12
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 4.7 55.1 from 2 benchmarks.
Widest category
Agentic work, 18.7 points apart on average over 6 shared benchmarks.
Widest single gap
ProofBench: Claude Sonnet 4.6 45.0% against GLM 4.7 6.0%, 39.0 points apart on a 0 to 100 scale.
Output price
Claude Sonnet 4.6 $15.00 against GLM 4.7 $2.20 per million output tokens, 6.8x apart.
Context window
Claude Sonnet 4.6 takes 1M tokens, GLM 4.7 205K.

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 4.7Ties
Coding91
Intelligence20
Agentic work51
Reasoning80
Math41
Knowledge83
Web design80
General163
All shared boards609
CodingLike-for-likeSix of these boards feed the Vibe Coding Index91
Coding benchmarks for Claude Sonnet 4.6 and GLM 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
LiveBench coding66.6%Not measuredOnly Claude Sonnet 4.6 measured
LMArena WebDev15231435Claude Sonnet 4.6
AA Coding Index63.045.3Claude Sonnet 4.6
LiveCodeBench (Vals AI)82.1%82.2%GLM 4.7
SWE-bench Verified (Vals AI)77.4%69.4%Claude Sonnet 4.6
Vibe Code Bench (Vals AI)55.8%Not measuredOnly Claude Sonnet 4.6 measured
Code migration (Vals AI)39.9%Not measuredOnly Claude Sonnet 4.6 measured
ProgramBench (Vals AI)0.5%Not measuredOnly Claude Sonnet 4.6 measured
Terminal-Bench 2.1 (Vals AI)57.3%Not measuredOnly Claude Sonnet 4.6 measured
SkillsBench (Vals AI)49.0%Not measuredOnly Claude Sonnet 4.6 measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GLM 4.7 measured
SciCode50.1%Not measuredOnly Claude Sonnet 4.6 measured
Terminal-Bench Hard (Artificial Analysis run)53.0%31.8%Claude Sonnet 4.6
Terminal-Bench53.4%33.4%Claude Sonnet 4.6
FrontierCode24.3%Not measuredOnly Claude Sonnet 4.6 measured
WeirdML66.1%Not measuredOnly Claude Sonnet 4.6 measured
ALE-BenchNot measured399.5Only GLM 4.7 measured
LMArena Text: coding15031454Claude Sonnet 4.6
LMArena Text: software and IT14911453Claude Sonnet 4.6
LMArena WebDev: React15121420Claude Sonnet 4.6
LMArena WebDev: HTML15271447Claude Sonnet 4.6
LMArena WebDev: from an image1529Not measuredOnly Claude Sonnet 4.6 measured
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Sonnet 4.6 and GLM 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
AA Intelligence Index30.122.2Claude Sonnet 4.6
Epoch Capabilities Index152.8143.6Claude Sonnet 4.6
Agentic workLike-for-likePublic boards, shown as published, kept out of the index51
Agentic work benchmarks for Claude Sonnet 4.6 and GLM 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
AA Agentic Index31.8Not measuredOnly Claude Sonnet 4.6 measured
Design Arena: agents building web apps1190Not measuredOnly Claude Sonnet 4.6 measured
Design Arena: agents building full-stack apps12131050Claude Sonnet 4.6
Design Arena: agents building mobile apps12121105Claude Sonnet 4.6
Design Arena: agents building Android apps11971112Claude Sonnet 4.6
Design Arena: agents building Godot games12261058Claude Sonnet 4.6
Design Arena: agents building games1177Not measuredOnly Claude Sonnet 4.6 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
Finance Agent (Vals AI)51.0%Not measuredOnly Claude Sonnet 4.6 measured
Tax Agent Bench (Vals AI)25.8%Not measuredOnly Claude Sonnet 4.6 measured
Legal Research Bench (Vals AI)38.5%Not measuredOnly Claude Sonnet 4.6 measured
Excel Modeling Benchmark (Vals AI)60.2%Not measuredOnly Claude Sonnet 4.6 measured
τ²-Bench Telecom79.5%95.9%GLM 4.7
APEX-Agents43.0%Not measuredOnly Claude Sonnet 4.6 measured
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$7,204$2,377Claude Sonnet 4.6
BrowseComp-PlusNot measured64.7%Only GLM 4.7 measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
Reasoning benchmarks for Claude Sonnet 4.6 and GLM 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
GPQA Diamond85.6%80.0%Claude Sonnet 4.6
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%85.9%Claude Sonnet 4.6
Humanity's Last Exam (Artificial Analysis run)33.6%27.4%Claude Sonnet 4.6
GPQA Diamond (Epoch AI run)87.4%83.3%Claude Sonnet 4.6
ARC-AGI86.5%Not measuredOnly Claude Sonnet 4.6 measured
ARC-AGI-260.4%Not measuredOnly Claude Sonnet 4.6 measured
SimpleBenchNot measured47.7%Only GLM 4.7 measured
Chess puzzles23.0%21.0%Claude Sonnet 4.6
Mystery game puzzles16.0%Not measuredOnly Claude Sonnet 4.6 measured
LMArena Text: hard prompts14851443Claude Sonnet 4.6
LMArena Text: expert15001424Claude Sonnet 4.6
LMArena Text: hard prompts in English14931452Claude Sonnet 4.6
LMArena Vision: diagrams1306Not measuredOnly Claude Sonnet 4.6 measured
LMArena Vision: homework1311Not measuredOnly Claude Sonnet 4.6 measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index41
Math benchmarks for Claude Sonnet 4.6 and GLM 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
AIME92.3%93.3%GLM 4.7
MGSM (Vals AI)Not measured88.2%Only GLM 4.7 measured
AA Math IndexNot measured95.0Only GLM 4.7 measured
AIME 2025 (Artificial Analysis run)Not measured95.0%Only GLM 4.7 measured
OTIS Mock AIME85.8%83.3%Claude Sonnet 4.6
ProofBench45.0%6.0%Claude Sonnet 4.6
LMArena Text: math14621424Claude Sonnet 4.6
LMArena Text: mathematical work14831411Claude Sonnet 4.6
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index83
Knowledge benchmarks for Claude Sonnet 4.6 and GLM 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
MMLU Pro87.3%82.7%Claude Sonnet 4.6
LegalBench (Vals AI)82.1%83.4%GLM 4.7
CaseLaw (Vals AI)64.0%54.9%Claude Sonnet 4.6
CorpFin (Vals AI)65.3%46.4%Claude Sonnet 4.6
TaxEval (Vals AI)77.1%68.8%Claude Sonnet 4.6
MortgageTax (Vals AI)67.7%Not measuredOnly Claude Sonnet 4.6 measured
MedQA (Vals AI)92.1%93.7%GLM 4.7
MedCode (Vals AI)Not measured32.8%Only GLM 4.7 measured
MMLU Pro (Artificial Analysis run)Not measured85.6%Only GLM 4.7 measured
SimpleQA Verified35.5%32.2%Claude Sonnet 4.6
LMArena Text: science14741457Claude Sonnet 4.6
LMArena Text: medicine and healthcare14511469GLM 4.7
LMArena Text: legal and government14701444Claude Sonnet 4.6
LMArena Text: business and finance14641429Claude Sonnet 4.6
FACTS Benchmark Suite37.0%Not measuredOnly Claude Sonnet 4.6 measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for Claude Sonnet 4.6 and GLM 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
Design Arena: websites12841225Claude Sonnet 4.6
Design Arena: UI components12691196Claude Sonnet 4.6
Design Arena: game dev12581188Claude Sonnet 4.6
Design Arena: data viz12781195Claude Sonnet 4.6
Design Arena: 3D12341190Claude Sonnet 4.6
Design Arena: all code categories12751216Claude Sonnet 4.6
Design Arena: SVG11961142Claude Sonnet 4.6
Design Arena: ASCII art12351165Claude Sonnet 4.6
LiveBench design71.8%Not measuredOnly Claude Sonnet 4.6 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index163
General benchmarks for Claude Sonnet 4.6 and GLM 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
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 measured68.6%Only GLM 4.7 measured
Vals Multimodal Index60.6%Not measuredOnly Claude Sonnet 4.6 measured
IFBench56.6%67.9%GLM 4.7
Long context reasoning (AA-LCR)80.0%71.0%Claude Sonnet 4.6
DTBench89.9%Not measuredOnly Claude Sonnet 4.6 measured
LMCA46.5%Not measuredOnly Claude Sonnet 4.6 measured
CL-benchNot measured15.9%Only GLM 4.7 measured
ExploitBench23.6%Not measuredOnly Claude Sonnet 4.6 measured
CL-bench LifeNot measured10.9%Only GLM 4.7 measured
LMArena Text14581435Claude Sonnet 4.6
LMArena Text: instruction following14761412Claude Sonnet 4.6
LMArena Text: creative writing14351401Claude Sonnet 4.6
LMArena Vision1283Not measuredOnly Claude Sonnet 4.6 measured
LMArena Text: English14721453Claude Sonnet 4.6
LMArena Text: non-English14401417Claude Sonnet 4.6
LMArena Text: Chinese14911495GLM 4.7
LMArena Text: German14281426Claude Sonnet 4.6
LMArena Text: Japanese14201439GLM 4.7
LMArena Text: Korean14101399Claude Sonnet 4.6
LMArena Text: French14651432Claude Sonnet 4.6
LMArena Text: Spanish14641434Claude Sonnet 4.6
LMArena Text: Russian14401423Claude Sonnet 4.6
LMArena Text: Polish14431435Claude Sonnet 4.6
LMArena Text: multi-turn14641446Claude Sonnet 4.6
LMArena Text: longer queries14791432Claude Sonnet 4.6
LMArena Text: writing and language14441411Claude Sonnet 4.6
LMArena Text: entertainment and media14311400Claude Sonnet 4.6
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 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 4.7
BenchmarkClaude Sonnet 4.6GLM 4.7Leader
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 4.7$0.0017Fits in one request

GLM 4.7 costs less

Repository review

50K input + 3K output tokens

Claude Sonnet 4.6$0.195Fits in one request
GLM 4.7$0.037Fits in one request

GLM 4.7 costs less

Agent loop

200K input + 10K output tokens

Claude Sonnet 4.6$0.750Fits in one request
GLM 4.7$0.142Exceeds the context window

GLM 4.7 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 4.7
SpecificationAnthropic Claude Sonnet 4.6Z.ai GLM 4.7
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedFebruary 17, 2026December 22, 2025
Context window1M205K
Input $/Mtok$3.00$0.60
Output $/Mtok$15.00$2.20
Coding index57.355.1
Independent measurements behind it52
Cost per solved task$1.68$0.29
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Sonnet 4.6 better than GLM 4.7 for coding?

Pick Claude Sonnet 4.6 for coding: it scores 57.3 on the Vibe Coding Index against 55.1 for GLM 4.7. Pick GLM 4.7 for output tokens 6.8x cheaper ($2.20 vs $15.00 per million) and a lower cost per solved task ($0.29 against $1.68).

Which is cheaper, Claude Sonnet 4.6 or GLM 4.7?

Claude Sonnet 4.6 costs $3.00 per million input tokens and $15.00 per million output tokens; GLM 4.7 costs $0.60 and $2.20. Per solved SWE-bench Verified task, Claude Sonnet 4.6 costs $1.68 and GLM 4.7 $0.29.

Which has the bigger context window, Claude Sonnet 4.6 or GLM 4.7?

Claude Sonnet 4.6, with 1M tokens against 205K.

How many benchmarks is the Claude Sonnet 4.6 vs GLM 4.7 comparison based on?

69 benchmarks have a result for both models as of October 22, 2026. Claude Sonnet 4.6's coding index rests on 5 independent benchmarks and GLM 4.7's on 2. Where only one model has a result, the page says so instead of naming a winner.

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