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Claude Opus 4.5 vs GLM 4.6

Claude Opus 4.5 leads GLM 4.6 on coding, 44.0 to 8.8 on the Vibe Coding Index, and GLM 4.6 costs 11.4x less per output token ($2.20 vs $25.00 per million). Updated October 21, 2026; 65 benchmarks have a result for both.

Replace Claude Opus 4.5 Replace GLM 4.6
Claude Opus 4.5Anthropic
Coding
44.0
Overall
55.7
Output $/M
$25.00
61
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
4
vs boards won of 65 shared

Claude Opus 4.5 or GLM 4.6: which to pick

Pick Claude Opus 4.5 for coding: it scores 44.0 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for output tokens 11.4x cheaper ($2.20 vs $25.00 per million) and a larger context window (205K against 200K tokens).

Model AClaude Opus 4.5Anthropic44.0/1003 independent benchmarks$1.37 per solved taskModel BGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task
Shared results
65
Claude Opus 4.5 only
43
GLM 4.6 only
4
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 Opus 4.5 44.0 from 3 benchmarks, GLM 4.6 8.8 from 2 benchmarks.
Widest category
Coding, 16.8 points apart on average over 10 shared benchmarks.
Widest single gap
Terminal-Bench: Claude Opus 4.5 63.1% against GLM 4.6 24.5%, 38.6 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.5 $25.00 against GLM 4.6 $2.20 per million output tokens, 11.4x apart.
Context window
Claude Opus 4.5 takes 200K tokens, GLM 4.6 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 Opus 4.5BarsGLM 4.6Ties
Coding100
Intelligence10
Agentic work50
Reasoning70
Math60
Knowledge82
Web design70
General172
All shared boards614
CodingLike-for-likeSix of these boards feed the Vibe Coding Index100
Coding benchmarks for Claude Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
SWE-bench Verified79.2%68.2%Claude Opus 4.5
SWE-bench (full test set)52.6%Not measuredOnly Claude Opus 4.5 measured
SWE-bench Multilingual70.7%Not measuredOnly Claude Opus 4.5 measured
LMArena WebDev14941341Claude Opus 4.5
AA Coding IndexNot measured45.8Only GLM 4.6 measured
LiveCodeBench (Vals AI)83.7%81.0%Claude Opus 4.5
SWE-bench Verified (Vals AI)76.4%Not measuredOnly Claude Opus 4.5 measured
Vibe Code Bench (Vals AI)20.6%3.1%Claude Opus 4.5
LiveCodeBench (Artificial Analysis run)87.1%69.5%Claude Opus 4.5
Terminal-Bench Hard (Artificial Analysis run)47.0%28.8%Claude Opus 4.5
Terminal-Bench63.1%24.5%Claude Opus 4.5
GSO-Bench26.5%Not measuredOnly Claude Opus 4.5 measured
WeirdML63.7%Not measuredOnly Claude Opus 4.5 measured
Cybench82.0%Not measuredOnly Claude Opus 4.5 measured
ALE-BenchNot measured340.8Only GLM 4.6 measured
LMArena Text: coding15031449Claude Opus 4.5
LMArena Text: software and IT14831455Claude Opus 4.5
LMArena WebDev: React1478Not measuredOnly Claude Opus 4.5 measured
LMArena WebDev: HTML15101350Claude Opus 4.5
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
AA Intelligence Index29.118.5Claude Opus 4.5
Epoch Capabilities Index150.1Not measuredOnly Claude Opus 4.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
Agentic work benchmarks for Claude Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
Design Arena: agents building web apps1159Not measuredOnly Claude Opus 4.5 measured
Design Arena: agents building full-stack apps11561029Claude Opus 4.5
Design Arena: agents building mobile apps11891096Claude Opus 4.5
Design Arena: agents building Android apps11751084Claude Opus 4.5
Design Arena: agents building Godot gamesNot measured1180Only GLM 4.6 measured
τ²-Bench Telecom89.5%76.9%Claude Opus 4.5
METR time horizons75.0%Not measuredOnly Claude Opus 4.5 measured
Remote Labor Index3.8%Not measuredOnly Claude Opus 4.5 measured
GDPval45.5%Not measuredOnly Claude Opus 4.5 measured
BALROG43.5%Not measuredOnly Claude Opus 4.5 measured
DeepResearch Bench54.8%Not measuredOnly Claude Opus 4.5 measured
OSWorld66.3%Not measuredOnly Claude Opus 4.5 measured
Vending-Bench 2$4,967Not measuredOnly Claude Opus 4.5 measured
Berkeley Function Calling Leaderboard (BFCL)77.5%72.4%Claude Opus 4.5
BrowseComp-PlusNot measured48.2%Only GLM 4.6 measured
Neither model has a result on the other 26 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for Claude Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
GPQA Diamond85.9%74.5%Claude Opus 4.5
MMMU Pro (Vals AI)83.0%Not measuredOnly Claude Opus 4.5 measured
GPQA Diamond (Artificial Analysis run)86.6%78.0%Claude Opus 4.5
Humanity's Last Exam (Artificial Analysis run)30.1%14.5%Claude Opus 4.5
GPQA Diamond (Epoch AI run)86.0%Not measuredOnly Claude Opus 4.5 measured
ARC-AGI80.0%Not measuredOnly Claude Opus 4.5 measured
ARC-AGI-237.6%Not measuredOnly Claude Opus 4.5 measured
SimpleBench62.0%Not measuredOnly Claude Opus 4.5 measured
Chess puzzles14.0%Not measuredOnly Claude Opus 4.5 measured
Mystery game puzzles22.0%Not measuredOnly Claude Opus 4.5 measured
EBR-bench14.3%Not measuredOnly Claude Opus 4.5 measured
VPCT40.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: hard prompts14761440Claude Opus 4.5
LMArena Text: expert14871432Claude Opus 4.5
LMArena Text: hard prompts in English14821445Claude Opus 4.5
Kagi LLM Benchmark80.2%45.7%Claude Opus 4.5
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for Claude Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
AIME95.4%92.7%Claude Opus 4.5
MGSM (Vals AI)95.2%89.8%Claude Opus 4.5
AA Math Index91.386.0Claude Opus 4.5
AIME 2025 (Artificial Analysis run)91.3%86.0%Claude Opus 4.5
OTIS Mock AIME86.1%Not measuredOnly Claude Opus 4.5 measured
FrontierMath, tiers 1 to 334.4%Not measuredOnly Claude Opus 4.5 measured
FrontierMath, tier 44.9%Not measuredOnly Claude Opus 4.5 measured
ProofBench36.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: math14631432Claude Opus 4.5
LMArena Text: mathematical work14681447Claude Opus 4.5
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index82
Knowledge benchmarks for Claude Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
MMLU Pro87.3%82.2%Claude Opus 4.5
LegalBench (Vals AI)84.6%79.6%Claude Opus 4.5
CaseLaw (Vals AI)62.6%Not measuredOnly Claude Opus 4.5 measured
CorpFin (Vals AI)65.1%56.8%Claude Opus 4.5
TaxEval (Vals AI)74.9%66.2%Claude Opus 4.5
MortgageTax (Vals AI)68.7%Not measuredOnly Claude Opus 4.5 measured
MedQA (Vals AI)95.9%92.2%Claude Opus 4.5
MedCode (Vals AI)49.2%Not measuredOnly Claude Opus 4.5 measured
MMLU Pro (Artificial Analysis run)89.5%82.9%Claude Opus 4.5
SimpleQA Verified45.7%Not measuredOnly Claude Opus 4.5 measured
GeoBench75.0%Not measuredOnly Claude Opus 4.5 measured
LMArena Text: science14541456GLM 4.6
LMArena Text: medicine and healthcare14441455GLM 4.6
LMArena Text: legal and government14591448Claude Opus 4.5
LMArena Text: business and finance14481416Claude Opus 4.5
FACTS Benchmark Suite43.9%Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for Claude Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
Design Arena: websites12471174Claude Opus 4.5
Design Arena: UI components12381148Claude Opus 4.5
Design Arena: game dev12291151Claude Opus 4.5
Design Arena: data viz12431161Claude Opus 4.5
Design Arena: 3D12141129Claude Opus 4.5
Design Arena: all code categories12421166Claude Opus 4.5
Design Arena: SVG11811109Claude Opus 4.5
Design Arena: ASCII art1190Not measuredOnly Claude Opus 4.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index172
General benchmarks for Claude Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
SAGE (Vals AI)52.1%Not measuredOnly Claude Opus 4.5 measured
MedScribe (Vals AI)85.3%Not measuredOnly Claude Opus 4.5 measured
IFBench58.0%43.4%Claude Opus 4.5
Long context reasoning (AA-LCR)77.3%54.0%Claude Opus 4.5
DTBench89.9%Not measuredOnly Claude Opus 4.5 measured
LMCA44.5%Not measuredOnly Claude Opus 4.5 measured
CL-bench21.1%Not measuredOnly Claude Opus 4.5 measured
Furniture assembly28.3%Not measuredOnly Claude Opus 4.5 measured
LMArena Text14511440Claude Opus 4.5
LMArena Text: instruction following14781410Claude Opus 4.5
LMArena Text: creative writing14451412Claude Opus 4.5
LMArena Text: English14611449Claude Opus 4.5
LMArena Text: non-English14381426Claude Opus 4.5
LMArena Text: Chinese14701499GLM 4.6
LMArena Text: German14491447Claude Opus 4.5
LMArena Text: Japanese14171393Claude Opus 4.5
LMArena Text: Korean14241400Claude Opus 4.5
LMArena Text: French14711459Claude Opus 4.5
LMArena Text: Spanish14571436Claude Opus 4.5
LMArena Text: Russian14471418Claude Opus 4.5
LMArena Text: Polish14391447GLM 4.6
LMArena Text: multi-turn14661427Claude Opus 4.5
LMArena Text: longer queries14791422Claude Opus 4.5
LMArena Text: writing and language14521415Claude Opus 4.5
LMArena Text: entertainment and media14341409Claude Opus 4.5
LMArena Document1462Not measuredOnly Claude Opus 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 Opus 4.5 and GLM 4.6
BenchmarkClaude Opus 4.5GLM 4.6Leader
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 Opus 4.5$0.018Fits in one request
GLM 4.6$0.0017Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.5$0.325Fits in one request
GLM 4.6$0.037Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.5$1.25Exceeds the context window
GLM 4.6$0.142Exceeds the context window

GLM 4.6 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 Opus 4.5 and GLM 4.6
SpecificationAnthropic Claude Opus 4.5Z.ai GLM 4.6
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedNovember 24, 2025September 30, 2025
Context window200K205K
Input $/Mtok$5.00$0.60
Output $/Mtok$25.00$2.20
Coding index44.08.8
Independent measurements behind it32
Cost per solved task$1.37Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.5 better than GLM 4.6 for coding?

Pick Claude Opus 4.5 for coding: it scores 44.0 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for output tokens 11.4x cheaper ($2.20 vs $25.00 per million) and a larger context window (205K against 200K tokens).

Which is cheaper, Claude Opus 4.5 or GLM 4.6?

Claude Opus 4.5 costs $5.00 per million input tokens and $25.00 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for Claude Opus 4.5 only.

Which has the bigger context window, Claude Opus 4.5 or GLM 4.6?

GLM 4.6, with 205K tokens against 200K.

How many benchmarks is the Claude Opus 4.5 vs GLM 4.6 comparison based on?

65 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.5's coding index rests on 3 independent benchmarks and GLM 4.6's on 2. Where only one model has a result, the page says so instead of naming a winner.

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