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Claude Sonnet 4.5 vs GLM 4.7

GLM 4.7 leads Claude Sonnet 4.5 on coding, 55.1 to 39.5 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 21, 2026; 65 benchmarks have a result for both.

Replace Claude Sonnet 4.5 Replace GLM 4.7
Claude Sonnet 4.5Anthropic
Coding
39.5
Overall
49.5
Output $/M
$15.00
41
GLM 4.7Z.ai
Coding
55.1
Overall
56.9
Output $/M
$2.20
23
vs boards won of 65 shared, 1 tied

Claude Sonnet 4.5 or GLM 4.7: which to pick

Pick GLM 4.7 for coding: it scores 55.1 on the Vibe Coding Index against 39.5 for Claude Sonnet 4.5, though on 2 benchmarks against 3.

Pick Claude Sonnet 4.5 for a larger context window (1M against 205K tokens) and work measured by AA Coding Index or SWE-bench Verified (Vals AI), where it leads.

Model AClaude Sonnet 4.5Anthropic39.5/1003 independent benchmarks$1.16 per solved taskModel BGLM 4.7Z.ai55.1/1002 independent benchmarks$0.29 per solved task
Shared results
65
Claude Sonnet 4.5 only
30
GLM 4.7 only
16
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 4.5 39.5 from 3 benchmarks, GLM 4.7 55.1 from 2 benchmarks.
Widest category
Math, 7.1 points apart on average over 6 shared benchmarks.
Widest single gap
MedScribe (Vals AI): Claude Sonnet 4.5 84.5% against GLM 4.7 68.6%, 15.9 points apart on a 0 to 100 scale.
Output price
Claude Sonnet 4.5 $15.00 against GLM 4.7 $2.20 per million output tokens, 6.8x apart.
Context window
Claude Sonnet 4.5 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 4.5BarsGLM 4.7Ties
Coding54
Intelligence11
Agentic work201 tie
Reasoning52
Math42
Knowledge93
Web design17
General144
All shared boards41231 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index54
Coding benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 4.7Leader
SWE-bench Verified74.8%Not measuredOnly Claude Sonnet 4.5 measured
SWE-bench Multilingual67.0%Not measuredOnly Claude Sonnet 4.5 measured
LMArena WebDev13941435GLM 4.7
AA Coding Index52.145.3Claude Sonnet 4.5
LiveCodeBench (Vals AI)73.0%82.2%GLM 4.7
SWE-bench Verified (Vals AI)70.0%69.4%Claude Sonnet 4.5
Vibe Code Bench (Vals AI)22.6%Not measuredOnly Claude Sonnet 4.5 measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GLM 4.7 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured31.8%Only GLM 4.7 measured
Terminal-Bench46.5%33.4%Claude Sonnet 4.5
GSO-Bench14.7%Not measuredOnly Claude Sonnet 4.5 measured
WeirdML47.7%Not measuredOnly Claude Sonnet 4.5 measured
Cybench60.0%Not measuredOnly Claude Sonnet 4.5 measured
ALE-BenchNot measured399.5Only GLM 4.7 measured
LMArena Text: coding14881454Claude Sonnet 4.5
LMArena Text: software and IT14731453Claude Sonnet 4.5
LMArena WebDev: React13861420GLM 4.7
LMArena WebDev: HTML13991447GLM 4.7
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 4.7Leader
AA Intelligence Index20.722.2GLM 4.7
Epoch Capabilities Index146.7143.6Claude Sonnet 4.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 4.7Leader
AA Agentic Index15.8Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: agents building web apps1059Not measuredOnly Claude Sonnet 4.5 measured
Design Arena: agents building full-stack apps10501050Tie
Design Arena: agents building mobile apps11371105Claude Sonnet 4.5
Design Arena: agents building Android appsNot measured1112Only GLM 4.7 measured
Design Arena: agents building Godot gamesNot measured1058Only GLM 4.7 measured
τ²-Bench TelecomNot measured95.9%Only GLM 4.7 measured
METR time horizons67.4%Not measuredOnly Claude Sonnet 4.5 measured
Remote Labor Index2.1%Not measuredOnly Claude Sonnet 4.5 measured
GDPval42.5%Not measuredOnly Claude Sonnet 4.5 measured
DeepResearch Bench52.6%Not measuredOnly Claude Sonnet 4.5 measured
OSWorld62.9%Not measuredOnly Claude Sonnet 4.5 measured
Vending-Bench 2$3,839$2,377Claude Sonnet 4.5
Berkeley Function Calling Leaderboard (BFCL)73.2%Not measuredOnly Claude Sonnet 4.5 measured
BrowseComp-PlusNot measured64.7%Only GLM 4.7 measured
Neither model has a result on the other 26 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index52
Reasoning benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 4.7Leader
GPQA Diamond81.6%80.0%Claude Sonnet 4.5
MMMU Pro (Vals AI)79.3%Not measuredOnly Claude Sonnet 4.5 measured
GPQA Diamond (Artificial Analysis run)Not measured85.9%Only GLM 4.7 measured
Humanity's Last Exam (Artificial Analysis run)Not measured27.4%Only GLM 4.7 measured
GPQA Diamond (Epoch AI run)82.3%83.3%GLM 4.7
ARC-AGI63.7%Not measuredOnly Claude Sonnet 4.5 measured
ARC-AGI-213.6%Not measuredOnly Claude Sonnet 4.5 measured
SimpleBench54.3%47.7%Claude Sonnet 4.5
Chess puzzles10.0%21.0%GLM 4.7
Mystery game puzzles17.0%Not measuredOnly Claude Sonnet 4.5 measured
EBR-bench2.4%Not measuredOnly Claude Sonnet 4.5 measured
VPCT39.8%Not measuredOnly Claude Sonnet 4.5 measured
LMArena Text: hard prompts14621443Claude Sonnet 4.5
LMArena Text: expert14831424Claude Sonnet 4.5
LMArena Text: hard prompts in English14711452Claude Sonnet 4.5
Kagi LLM Benchmark57.9%Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index42
Math benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 4.7Leader
AIME88.2%93.3%GLM 4.7
MGSM (Vals AI)94.3%88.2%Claude Sonnet 4.5
AA Math IndexNot measured95.0Only GLM 4.7 measured
AIME 2025 (Artificial Analysis run)Not measured95.0%Only GLM 4.7 measured
OTIS Mock AIME77.8%83.3%GLM 4.7
FrontierMath, tiers 1 to 323.9%Not measuredOnly Claude Sonnet 4.5 measured
FrontierMath, tier 42.4%Not measuredOnly Claude Sonnet 4.5 measured
ProofBench19.0%6.0%Claude Sonnet 4.5
MATH level 597.7%Not measuredOnly Claude Sonnet 4.5 measured
LMArena Text: math14491424Claude Sonnet 4.5
LMArena Text: mathematical work14621411Claude Sonnet 4.5
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index93
Knowledge benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 4.7Leader
MMLU Pro87.4%82.7%Claude Sonnet 4.5
LegalBench (Vals AI)84.1%83.4%Claude Sonnet 4.5
CaseLaw (Vals AI)62.2%54.9%Claude Sonnet 4.5
CorpFin (Vals AI)62.0%46.4%Claude Sonnet 4.5
TaxEval (Vals AI)73.3%68.8%Claude Sonnet 4.5
MortgageTax (Vals AI)64.0%Not measuredOnly Claude Sonnet 4.5 measured
MedQA (Vals AI)94.7%93.7%Claude Sonnet 4.5
MedCode (Vals AI)44.1%32.8%Claude Sonnet 4.5
MMLU Pro (Artificial Analysis run)Not measured85.6%Only GLM 4.7 measured
SimpleQA Verified30.7%32.2%GLM 4.7
LMArena Text: science14481457GLM 4.7
LMArena Text: medicine and healthcare14441469GLM 4.7
LMArena Text: legal and government14511444Claude Sonnet 4.5
LMArena Text: business and finance14401429Claude Sonnet 4.5
FACTS Benchmark Suite40.6%Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index17
Web design benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 4.7Leader
Design Arena: websites11901226GLM 4.7
Design Arena: UI components11731199GLM 4.7
Design Arena: game dev11661189GLM 4.7
Design Arena: data viz11671195GLM 4.7
Design Arena: 3D11581191GLM 4.7
Design Arena: all code categories11831217GLM 4.7
Design Arena: SVG11151143GLM 4.7
Design Arena: ASCII art12051165Claude Sonnet 4.5
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index144
General benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 4.7Leader
SAGE (Vals AI)36.1%Not measuredOnly Claude Sonnet 4.5 measured
MedScribe (Vals AI)84.5%68.6%Claude Sonnet 4.5
IFBenchNot measured67.9%Only GLM 4.7 measured
Long context reasoning (AA-LCR)Not measured71.0%Only GLM 4.7 measured
DTBench83.2%Not measuredOnly Claude Sonnet 4.5 measured
LMCA38.8%Not measuredOnly Claude Sonnet 4.5 measured
CL-benchNot measured15.9%Only GLM 4.7 measured
CL-bench LifeNot measured10.9%Only GLM 4.7 measured
LMArena Text14381435Claude Sonnet 4.5
LMArena Text: instruction following14591412Claude Sonnet 4.5
LMArena Text: creative writing14421401Claude Sonnet 4.5
LMArena Text: English14501453GLM 4.7
LMArena Text: non-English14251417Claude Sonnet 4.5
LMArena Text: Chinese14601495GLM 4.7
LMArena Text: German14271426Claude Sonnet 4.5
LMArena Text: Japanese13901439GLM 4.7
LMArena Text: Korean14021399Claude Sonnet 4.5
LMArena Text: French14591432Claude Sonnet 4.5
LMArena Text: Spanish14581434Claude Sonnet 4.5
LMArena Text: Russian14371423Claude Sonnet 4.5
LMArena Text: Polish14231435GLM 4.7
LMArena Text: multi-turn14651446Claude Sonnet 4.5
LMArena Text: longer queries14751432Claude Sonnet 4.5
LMArena Text: writing and language14421411Claude Sonnet 4.5
LMArena Text: entertainment and media14281400Claude Sonnet 4.5
LMArena Document1450Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 20 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Sonnet 4.5 and GLM 4.7
BenchmarkClaude Sonnet 4.5GLM 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 4.5$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 4.5$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 4.5$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 4.5 and GLM 4.7
SpecificationAnthropic Claude Sonnet 4.5Z.ai GLM 4.7
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedSeptember 29, 2025December 22, 2025
Context window1M205K
Input $/Mtok$3.00$0.60
Output $/Mtok$15.00$2.20
Coding index39.555.1
Independent measurements behind it32
Cost per solved task$1.16$0.29
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Sonnet 4.5 better than GLM 4.7 for coding?

Pick GLM 4.7 for coding: it scores 55.1 on the Vibe Coding Index against 39.5 for Claude Sonnet 4.5, though on 2 benchmarks against 3. Pick Claude Sonnet 4.5 for a larger context window (1M against 205K tokens) and work measured by AA Coding Index or SWE-bench Verified (Vals AI), where it leads.

Which is cheaper, Claude Sonnet 4.5 or GLM 4.7?

Claude Sonnet 4.5 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 4.5 costs $1.16 and GLM 4.7 $0.29.

Which has the bigger context window, Claude Sonnet 4.5 or GLM 4.7?

Claude Sonnet 4.5, with 1M tokens against 205K.

How many benchmarks is the Claude Sonnet 4.5 vs GLM 4.7 comparison based on?

65 benchmarks have a result for both models as of October 21, 2026. Claude Sonnet 4.5's coding index rests on 3 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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