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Claude Opus 5.5 vs GLM 4.6

Claude Opus 5.5 leads GLM 4.6 on coding, 88.8 to 8.8 on the Vibe Coding Index, and GLM 4.6 costs 9.1x less per output token ($2.20 vs $20.00 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Claude Opus 5.5Anthropic
Coding
88.8
Overall
87.1
Output $/M
$20.00
40
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
0
vs boards won of 40 shared

Claude Opus 5.5 or GLM 4.6: which to pick

Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for output tokens 9.1x cheaper ($2.20 vs $20.00 per million).

Shared results
40
Claude Opus 5.5 only
69
GLM 4.6 only
29
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 5.5 88.8 from 5 benchmarks, GLM 4.6 8.8 from 2 benchmarks.
Widest category
Coding, 47.6 points apart on average over 6 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Claude Opus 5.5 90.3% against GLM 4.6 3.1%, 87.2 points apart on a 0 to 100 scale.
Output price
Claude Opus 5.5 $20.00 against GLM 4.6 $2.20 per million output tokens, 9.1x apart.
Context window
Claude Opus 5.5 takes 1M 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 5.5BarsGLM 4.6Ties
Coding60
Intelligence10
Agentic work10
Reasoning40
Math20
Knowledge40
Web design70
General150
All shared boards400
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
Coding benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 4.6Leader
SWE-bench VerifiedNot measured68.2%Only GLM 4.6 measured
LiveBench coding96.3%Not measuredOnly Claude Opus 5.5 measured
LMArena WebDev18071341Claude Opus 5.5
AA Coding IndexNot measured45.8Only GLM 4.6 measured
LiveCodeBench (Vals AI)Not measured81.0%Only GLM 4.6 measured
Terminal-Bench 4 (Vals AI)65.2%Not measuredOnly Claude Opus 5.5 measured
Vibe Code Bench (Vals AI)90.3%3.1%Claude Opus 5.5
Code migration (Vals AI)66.7%Not measuredOnly Claude Opus 5.5 measured
ProgramBench (Vals AI)18.5%Not measuredOnly Claude Opus 5.5 measured
IOI (Vals AI)95.1%Not measuredOnly Claude Opus 5.5 measured
Terminal-Bench 2.1 (Vals AI)87.6%Not measuredOnly Claude Opus 5.5 measured
SWE-bench Multimodal (Vals AI)70.2%Not measuredOnly Claude Opus 5.5 measured
Vibe Code Bench 1-100 (Vals AI)30.4%Not measuredOnly Claude Opus 5.5 measured
CyberBench (Vals AI)74.6%Not measuredOnly Claude Opus 5.5 measured
LiveCodeBench (Artificial Analysis run)Not measured69.5%Only GLM 4.6 measured
SciCode66.9%Not measuredOnly Claude Opus 5.5 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured28.8%Only GLM 4.6 measured
Terminal-BenchNot measured24.5%Only GLM 4.6 measured
FrontierCode54.6%Not measuredOnly Claude Opus 5.5 measured
FrontierSWE62.3%Not measuredOnly Claude Opus 5.5 measured
MirrorCode77.4%Not measuredOnly Claude Opus 5.5 measured
ALE-Bench2147.4340.8Claude Opus 5.5
LMArena Text: coding15451449Claude Opus 5.5
LMArena Text: software and IT15381455Claude Opus 5.5
LMArena WebDev: React1855Not measuredOnly Claude Opus 5.5 measured
LMArena WebDev: HTML17531350Claude Opus 5.5
LMArena WebDev: from an image1753Not measuredOnly Claude Opus 5.5 measured
SciCode18.5%Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 11 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 4.6Leader
AA Intelligence Index57.618.5Claude Opus 5.5
Epoch Capabilities Index168.8Not measuredOnly Claude Opus 5.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 4.6Leader
Design Arena: agents building web apps1316Not measuredOnly Claude Opus 5.5 measured
Design Arena: agents building full-stack appsNot measured1029Only GLM 4.6 measured
Design Arena: agents building mobile apps13081096Claude Opus 5.5
Design Arena: agents building Android appsNot measured1084Only GLM 4.6 measured
Design Arena: agents building Godot gamesNot measured1180Only GLM 4.6 measured
Design Arena: spreadsheets1368Not measuredOnly Claude Opus 5.5 measured
LiveBench research85.0%Not measuredOnly Claude Opus 5.5 measured
LiveBench browser80.0%Not measuredOnly Claude Opus 5.5 measured
LiveBench long agentic85.0%Not measuredOnly Claude Opus 5.5 measured
SREBench (Vals AI)33.6%Not measuredOnly Claude Opus 5.5 measured
Finance Agent (Vals AI)58.6%Not measuredOnly Claude Opus 5.5 measured
Tax Agent Bench (Vals AI)45.6%Not measuredOnly Claude Opus 5.5 measured
Legal Research Bench (Vals AI)50.5%Not measuredOnly Claude Opus 5.5 measured
Harvey's Legal Agent Benchmark (Vals AI)9.2%Not measuredOnly Claude Opus 5.5 measured
Excel Modeling Benchmark (Vals AI)75.9%Not measuredOnly Claude Opus 5.5 measured
BioMysteryBench (Vals AI)79.3%Not measuredOnly Claude Opus 5.5 measured
Terminal-Bench-Science (Vals AI)47.1%Not measuredOnly Claude Opus 5.5 measured
Vals Science Index58.7%Not measuredOnly Claude Opus 5.5 measured
Time Horizon Index (Vals AI)91.3%Not measuredOnly Claude Opus 5.5 measured
CUA-bench (Vals AI)14.0%Not measuredOnly Claude Opus 5.5 measured
Robo-bench (Vals AI)14.6%Not measuredOnly Claude Opus 5.5 measured
τ²-Bench TelecomNot measured76.9%Only GLM 4.6 measured
APEX-Agents73.5%Not measuredOnly Claude Opus 5.5 measured
Remote Labor Index21.3%Not measuredOnly Claude Opus 5.5 measured
SpireClimb3.3%Not measuredOnly Claude Opus 5.5 measured
Vending-Bench 2$9,235Not measuredOnly Claude Opus 5.5 measured
LMArena Search1213Not measuredOnly Claude Opus 5.5 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured72.4%Only GLM 4.6 measured
BrowseComp-PlusNot measured48.2%Only GLM 4.6 measured
Neither model has a result on the other 12 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 4.6Leader
GPQA DiamondNot measured74.5%Only GLM 4.6 measured
LiveBench reasoning92.2%Not measuredOnly Claude Opus 5.5 measured
MysteryMechanism (Vals AI)49.5%Not measuredOnly Claude Opus 5.5 measured
GPQA Diamond (Artificial Analysis run)Not measured78.0%Only GLM 4.6 measured
Humanity's Last Exam (Artificial Analysis run)61.4%14.5%Claude Opus 5.5
GPQA Diamond (Epoch AI run)90.6%Not measuredOnly Claude Opus 5.5 measured
ARC-AGI98.5%Not measuredOnly Claude Opus 5.5 measured
ARC-AGI-293.3%Not measuredOnly Claude Opus 5.5 measured
Chess puzzles67.0%Not measuredOnly Claude Opus 5.5 measured
Mystery game puzzles71.0%Not measuredOnly Claude Opus 5.5 measured
EBR-bench71.4%Not measuredOnly Claude Opus 5.5 measured
LMArena Text: hard prompts15361440Claude Opus 5.5
LMArena Text: expert15491432Claude Opus 5.5
LMArena Text: hard prompts in English15351445Claude Opus 5.5
LMArena Vision: diagrams1345Not measuredOnly Claude Opus 5.5 measured
LMArena Vision: homework1362Not measuredOnly Claude Opus 5.5 measured
Kagi LLM BenchmarkNot measured45.7%Only GLM 4.6 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 4.6Leader
AIMENot measured92.7%Only GLM 4.6 measured
MGSM (Vals AI)Not measured89.8%Only GLM 4.6 measured
AA Math IndexNot measured86.0Only GLM 4.6 measured
AIME 2025 (Artificial Analysis run)Not measured86.0%Only GLM 4.6 measured
OTIS Mock AIME100.0%Not measuredOnly Claude Opus 5.5 measured
FrontierMath, tiers 1 to 391.2%Not measuredOnly Claude Opus 5.5 measured
FrontierMath, tier 495.0%Not measuredOnly Claude Opus 5.5 measured
ProofBench100.0%Not measuredOnly Claude Opus 5.5 measured
LMArena Text: math15181432Claude Opus 5.5
LMArena Text: mathematical work15161447Claude Opus 5.5
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 4.6Leader
MMLU ProNot measured82.2%Only GLM 4.6 measured
LegalBench (Vals AI)Not measured79.6%Only GLM 4.6 measured
CorpFin (Vals AI)Not measured56.8%Only GLM 4.6 measured
TaxEval (Vals AI)Not measured66.2%Only GLM 4.6 measured
MedQA (Vals AI)Not measured92.2%Only GLM 4.6 measured
MedCode (Vals AI)49.8%Not measuredOnly Claude Opus 5.5 measured
MMLU Pro (Artificial Analysis run)Not measured82.9%Only GLM 4.6 measured
SimpleQA Verified72.2%Not measuredOnly Claude Opus 5.5 measured
LMArena Text: science15241456Claude Opus 5.5
LMArena Text: medicine and healthcare15091455Claude Opus 5.5
LMArena Text: legal and government15181448Claude Opus 5.5
LMArena Text: business and finance14941416Claude Opus 5.5
FACTS Benchmark Suite65.3%Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 4.6Leader
Design Arena: websites13351174Claude Opus 5.5
Design Arena: UI components13851145Claude Opus 5.5
Design Arena: game dev14611150Claude Opus 5.5
Design Arena: data viz13971161Claude Opus 5.5
Design Arena: 3D14761128Claude Opus 5.5
Design Arena: all code categories13901165Claude Opus 5.5
Design Arena: SVG13291108Claude Opus 5.5
LiveBench design86.9%Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index150
General benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 4.6Leader
Vals Index70.2%Not measuredOnly Claude Opus 5.5 measured
LiveBench data analysis80.3%Not measuredOnly Claude Opus 5.5 measured
Public Benefits Bench (Vals AI)70.6%Not measuredOnly Claude Opus 5.5 measured
SAGE (Vals AI)45.8%Not measuredOnly Claude Opus 5.5 measured
MedScribe (Vals AI)91.4%Not measuredOnly Claude Opus 5.5 measured
IFBenchNot measured43.4%Only GLM 4.6 measured
Long context reasoning (AA-LCR)84.7%54.0%Claude Opus 5.5
DTBench98.9%Not measuredOnly Claude Opus 5.5 measured
LMCA68.2%Not measuredOnly Claude Opus 5.5 measured
Furniture assembly83.3%Not measuredOnly Claude Opus 5.5 measured
LMArena Text15161440Claude Opus 5.5
LMArena Text: instruction following15371410Claude Opus 5.5
LMArena Text: creative writing15351412Claude Opus 5.5
LMArena Vision1321Not measuredOnly Claude Opus 5.5 measured
LMArena Text: English15191449Claude Opus 5.5
LMArena Text: non-English15071426Claude Opus 5.5
LMArena Text: Chinese15821499Claude Opus 5.5
LMArena Text: GermanNot measured1447Only GLM 4.6 measured
LMArena Text: Japanese15341393Claude Opus 5.5
LMArena Text: KoreanNot measured1400Only GLM 4.6 measured
LMArena Text: French14931459Claude Opus 5.5
LMArena Text: Spanish15081436Claude Opus 5.5
LMArena Text: Russian15171418Claude Opus 5.5
LMArena Text: PolishNot measured1447Only GLM 4.6 measured
LMArena Text: multi-turn15011427Claude Opus 5.5
LMArena Text: longer queries15321422Claude Opus 5.5
LMArena Text: writing and language15321415Claude Opus 5.5
LMArena Text: entertainment and media15151409Claude Opus 5.5
LMArena Vision: English1317Not measuredOnly Claude Opus 5.5 measured
LMArena Vision: reading text1326Not measuredOnly Claude Opus 5.5 measured
LMArena Vision: creative writing1320Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 5.5 and GLM 4.6
BenchmarkClaude Opus 5.5GLM 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 5.5$0.014Fits 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 5.5$0.260Fits 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 5.5$1.00Fits in one request
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 5.5 and GLM 4.6
SpecificationAnthropic Claude Opus 5.5Z.ai GLM 4.6
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedSeptember 22, 2026September 30, 2025
Context window1M205K
Input $/Mtok$4.00$0.60
Output $/Mtok$20.00$2.20
Coding index88.88.8
Independent measurements behind it52
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 5.5 better than GLM 4.6 for coding?

Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for output tokens 9.1x cheaper ($2.20 vs $20.00 per million).

Which is cheaper, Claude Opus 5.5 or GLM 4.6?

Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for neither of them.

Which has the bigger context window, Claude Opus 5.5 or GLM 4.6?

Claude Opus 5.5, with 1M tokens against 205K.

How many benchmarks is the Claude Opus 5.5 vs GLM 4.6 comparison based on?

40 benchmarks have a result for both models as of October 22, 2026. Claude Opus 5.5's coding index rests on 5 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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