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Claude Sonnet 4.5 vs GLM 5.1

GLM 5.1 leads Claude Sonnet 4.5 on coding, 49.2 to 39.5 on the Vibe Coding Index, and GLM 5.1 costs 3.4x less per output token ($4.40 vs $15.00 per million). Updated October 22, 2026; 67 benchmarks have a result for both.

Replace Claude Sonnet 4.5 Replace GLM 5.1
Claude Sonnet 4.5Anthropic
Coding
39.5
Overall
49.5
Output $/M
$15.00
10
GLM 5.1Z.ai
Coding
49.2
Overall
57.5
Output $/M
$4.40
57
vs boards won of 67 shared

Claude Sonnet 4.5 or GLM 5.1: which to pick

Pick GLM 5.1 for coding: it scores 49.2 on the Vibe Coding Index against 39.5 for Claude Sonnet 4.5.

Pick Claude Sonnet 4.5 for a larger context window (1M against 205K tokens) and work measured by LMArena Text: coding or LMArena Text: expert, where it leads.

Model AClaude Sonnet 4.5Anthropic39.5/1003 independent benchmarks$1.16 per solved taskModel BGLM 5.1Z.ai49.2/1003 independent benchmarks$0.60 per solved task
Shared results
67
Claude Sonnet 4.5 only
28
GLM 5.1 only
22
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 5.1 49.2 from 3 benchmarks.
Widest category
Web design, 14.9 points apart on average over 8 shared benchmarks.
Widest single gap
Design Arena: data viz: Claude Sonnet 4.5 1167 against GLM 5.1 1366, 24.9 points apart on a 0 to 100 scale.
Output price
Claude Sonnet 4.5 $15.00 against GLM 5.1 $4.40 per million output tokens, 3.4x apart.
Context window
Claude Sonnet 4.5 takes 1M tokens, GLM 5.1 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 5.1Ties
Coding19
Intelligence02
Agentic work05
Reasoning16
Math06
Knowledge47
Web design17
General315
All shared boards1057
CodingLike-for-likeSix of these boards feed the Vibe Coding Index19
Coding benchmarks for Claude Sonnet 4.5 and GLM 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
SWE-bench Verified74.8%Not measuredOnly Claude Sonnet 4.5 measured
SWE-bench Multilingual67.0%Not measuredOnly Claude Sonnet 4.5 measured
LMArena WebDev13941508GLM 5.1
AA Coding Index52.155.8GLM 5.1
LiveCodeBench (Vals AI)73.0%81.4%GLM 5.1
SWE-bench Verified (Vals AI)70.0%76.4%GLM 5.1
Vibe Code Bench (Vals AI)22.6%31.5%GLM 5.1
Code migration (Vals AI)Not measured25.8%Only GLM 5.1 measured
ProgramBench (Vals AI)Not measured0.0%Only GLM 5.1 measured
Terminal-Bench 2.1 (Vals AI)Not measured56.9%Only GLM 5.1 measured
SciCodeNot measured44.8%Only GLM 5.1 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured43.2%Only GLM 5.1 measured
Terminal-Bench46.5%Not measuredOnly Claude Sonnet 4.5 measured
GSO-Bench14.7%Not measuredOnly Claude Sonnet 4.5 measured
WeirdML47.7%57.1%GLM 5.1
Cybench60.0%Not measuredOnly Claude Sonnet 4.5 measured
ALE-BenchNot measured887.1Only GLM 5.1 measured
LMArena Text: coding14881485Claude Sonnet 4.5
LMArena Text: software and IT14731484GLM 5.1
LMArena WebDev: React13861505GLM 5.1
LMArena WebDev: HTML13991508GLM 5.1
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Claude Sonnet 4.5 and GLM 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
AA Intelligence Index20.726.1GLM 5.1
Epoch Capabilities Index146.7149.8GLM 5.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index05
Agentic work benchmarks for Claude Sonnet 4.5 and GLM 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
AA Agentic Index15.823.9GLM 5.1
Design Arena: agents building web apps10601175GLM 5.1
Design Arena: agents building full-stack apps10501167GLM 5.1
Design Arena: agents building mobile apps11371162GLM 5.1
Design Arena: agents building Android appsNot measured1182Only GLM 5.1 measured
Design Arena: agents building Godot gamesNot measured1053Only GLM 5.1 measured
Design Arena: agents building gamesNot measured1164Only GLM 5.1 measured
Design Arena: HTML slidesNot measured1120Only GLM 5.1 measured
Design Arena: PowerPoint slidesNot measured1163Only GLM 5.1 measured
Design Arena: spreadsheetsNot measured1315Only GLM 5.1 measured
Finance Agent (Vals AI)Not measured44.8%Only GLM 5.1 measured
Legal Research Bench (Vals AI)Not measured27.9%Only GLM 5.1 measured
τ²-Bench TelecomNot measured97.7%Only GLM 5.1 measured
APEX-AgentsNot measured40.9%Only GLM 5.1 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$5,634GLM 5.1
Berkeley Function Calling Leaderboard (BFCL)73.2%Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index16
Reasoning benchmarks for Claude Sonnet 4.5 and GLM 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
GPQA Diamond81.6%84.5%GLM 5.1
MMMU Pro (Vals AI)79.3%Not measuredOnly Claude Sonnet 4.5 measured
GPQA Diamond (Artificial Analysis run)Not measured86.8%Only GLM 5.1 measured
Humanity's Last Exam (Artificial Analysis run)Not measured30.1%Only GLM 5.1 measured
GPQA Diamond (Epoch AI run)82.3%89.9%GLM 5.1
ARC-AGI63.7%Not measuredOnly Claude Sonnet 4.5 measured
ARC-AGI-213.6%Not measuredOnly Claude Sonnet 4.5 measured
SimpleBench54.3%55.1%GLM 5.1
Chess puzzles10.0%20.0%GLM 5.1
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 prompts14621473GLM 5.1
LMArena Text: expert14831478Claude Sonnet 4.5
LMArena Text: hard prompts in English14711482GLM 5.1
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 index06
Math benchmarks for Claude Sonnet 4.5 and GLM 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
AIME88.2%91.9%GLM 5.1
MGSM (Vals AI)94.3%Not measuredOnly Claude Sonnet 4.5 measured
OTIS Mock AIME77.8%93.3%GLM 5.1
FrontierMath, tiers 1 to 323.9%36.8%GLM 5.1
FrontierMath, tier 42.4%Not measuredOnly Claude Sonnet 4.5 measured
ProofBench19.0%22.2%GLM 5.1
MATH level 597.7%Not measuredOnly Claude Sonnet 4.5 measured
LMArena Text: math14491473GLM 5.1
LMArena Text: mathematical work14621470GLM 5.1
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index47
Knowledge benchmarks for Claude Sonnet 4.5 and GLM 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
MMLU Pro87.4%86.9%Claude Sonnet 4.5
LegalBench (Vals AI)84.1%84.4%GLM 5.1
CaseLaw (Vals AI)62.2%51.5%Claude Sonnet 4.5
CorpFin (Vals AI)62.0%64.5%GLM 5.1
TaxEval (Vals AI)73.3%71.2%Claude Sonnet 4.5
MortgageTax (Vals AI)64.0%Not measuredOnly Claude Sonnet 4.5 measured
MedQA (Vals AI)94.7%Not measuredOnly Claude Sonnet 4.5 measured
MedCode (Vals AI)44.1%41.6%Claude Sonnet 4.5
SimpleQA Verified30.7%34.0%GLM 5.1
LMArena Text: science14481478GLM 5.1
LMArena Text: medicine and healthcare14441474GLM 5.1
LMArena Text: legal and government14511465GLM 5.1
LMArena Text: business and finance14401452GLM 5.1
FACTS Benchmark Suite40.6%Not measuredOnly Claude Sonnet 4.5 measured
Neither model has a result on the other 4 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 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
Design Arena: websites11891290GLM 5.1
Design Arena: UI components11701292GLM 5.1
Design Arena: game dev11661265GLM 5.1
Design Arena: data viz11671366GLM 5.1
Design Arena: 3D11571336GLM 5.1
Design Arena: all code categories11821268GLM 5.1
Design Arena: SVG11151218GLM 5.1
Design Arena: ASCII art12051141Claude 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 index315
General benchmarks for Claude Sonnet 4.5 and GLM 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
Public Benefits Bench (Vals AI)Not measured61.8%Only GLM 5.1 measured
SAGE (Vals AI)36.1%Not measuredOnly Claude Sonnet 4.5 measured
MedScribe (Vals AI)84.5%72.3%Claude Sonnet 4.5
IFBenchNot measured76.3%Only GLM 5.1 measured
Long context reasoning (AA-LCR)Not measured73.7%Only GLM 5.1 measured
DTBench83.2%Not measuredOnly Claude Sonnet 4.5 measured
LMCA38.8%Not measuredOnly Claude Sonnet 4.5 measured
ExploitBenchNot measured18.1%Only GLM 5.1 measured
LMArena Text14381463GLM 5.1
LMArena Text: instruction following14591453Claude Sonnet 4.5
LMArena Text: creative writing14421453GLM 5.1
LMArena Text: English14501476GLM 5.1
LMArena Text: non-English14251448GLM 5.1
LMArena Text: Chinese14601515GLM 5.1
LMArena Text: German14271467GLM 5.1
LMArena Text: Japanese13901435GLM 5.1
LMArena Text: Korean14021424GLM 5.1
LMArena Text: French14591470GLM 5.1
LMArena Text: Spanish14581468GLM 5.1
LMArena Text: Russian14371454GLM 5.1
LMArena Text: Polish14231449GLM 5.1
LMArena Text: multi-turn14651473GLM 5.1
LMArena Text: longer queries14751467Claude Sonnet 4.5
LMArena Text: writing and language14421454GLM 5.1
LMArena Text: entertainment and media14281442GLM 5.1
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 5.1
BenchmarkClaude Sonnet 4.5GLM 5.1Leader
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 5.1$0.0036Fits in one request

GLM 5.1 costs less

Repository review

50K input + 3K output tokens

Claude Sonnet 4.5$0.195Fits in one request
GLM 5.1$0.083Fits in one request

GLM 5.1 costs less

Agent loop

200K input + 10K output tokens

Claude Sonnet 4.5$0.750Fits in one request
GLM 5.1$0.324Exceeds the context window

GLM 5.1 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 5.1
SpecificationAnthropic Claude Sonnet 4.5Z.ai GLM 5.1
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedSeptember 29, 2025April 7, 2026
Context window1M205K
Input $/Mtok$3.00$1.40
Output $/Mtok$15.00$4.40
Coding index39.549.2
Independent measurements behind it33
Cost per solved task$1.16$0.60
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Sonnet 4.5 better than GLM 5.1 for coding?

Pick GLM 5.1 for coding: it scores 49.2 on the Vibe Coding Index against 39.5 for Claude Sonnet 4.5. Pick Claude Sonnet 4.5 for a larger context window (1M against 205K tokens) and work measured by LMArena Text: coding or LMArena Text: expert, where it leads.

Which is cheaper, Claude Sonnet 4.5 or GLM 5.1?

Claude Sonnet 4.5 costs $3.00 per million input tokens and $15.00 per million output tokens; GLM 5.1 costs $1.40 and $4.40. Per solved SWE-bench Verified task, Claude Sonnet 4.5 costs $1.16 and GLM 5.1 $0.60.

Which has the bigger context window, Claude Sonnet 4.5 or GLM 5.1?

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

How many benchmarks is the Claude Sonnet 4.5 vs GLM 5.1 comparison based on?

67 benchmarks have a result for both models as of October 22, 2026. Claude Sonnet 4.5's coding index rests on 3 independent benchmarks and GLM 5.1's on 3. Where only one model has a result, the page says so instead of naming a winner.

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