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Claude Opus 4.1 vs GLM 4.6

Claude Opus 4.1 leads GLM 4.6 on the Artificial Analysis Intelligence Index, 22.8 to 18.5, and GLM 4.6 costs 34.1x less per output token ($2.20 vs $75.00 per million). Updated October 22, 2026; 47 benchmarks have a result for both.

Replace Claude Opus 4.1 Replace GLM 4.6
Claude Opus 4.1Anthropic
Coding
No data
Overall
50.2
Output $/M
$75.00
29
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
18
vs boards won of 47 shared

Claude Opus 4.1 or GLM 4.6: which to pick

Only GLM 4.6 has a coding score, 8.8 on the Vibe Coding Index; Claude Opus 4.1 has none, so the two cannot be ranked on coding.

Pick Claude Opus 4.1 for work measured by LMArena WebDev or Terminal-Bench, where it leads.

Model AClaude Opus 4.1AnthropicNot benchmarked1 independent benchmarkNo cost per solved taskModel BGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task
Shared results
47
Claude Opus 4.1 only
26
GLM 4.6 only
22
Like-for-like categories
7 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 4.1 not benchmarked, GLM 4.6 8.8 from 2 benchmarks.
Widest category
Coding, 8.1 points apart on average over 6 shared benchmarks.
Widest single gap
LiveCodeBench (Vals AI): Claude Opus 4.1 66.5% against GLM 4.6 81.0%, 14.6 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.1 $75.00 against GLM 4.6 $2.20 per million output tokens, 34.1x apart.
Context window
Claude Opus 4.1 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 4.1BarsGLM 4.6Ties
Coding51
Intelligence10
Reasoning40
Math13
Knowledge44
Web design70
General710
All shared boards2918
CodingLike-for-likeSix of these boards feed the Vibe Coding Index51
Coding benchmarks for Claude Opus 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 4.6Leader
SWE-bench VerifiedNot measured68.2%Only GLM 4.6 measured
LMArena WebDev13901341Claude Opus 4.1
AA Coding IndexNot measured45.8Only GLM 4.6 measured
LiveCodeBench (Vals AI)66.5%81.0%GLM 4.6
Vibe Code Bench (Vals AI)Not measured3.1%Only GLM 4.6 measured
LiveCodeBench (Artificial Analysis run)Not measured69.5%Only GLM 4.6 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured28.8%Only GLM 4.6 measured
Terminal-Bench38.0%24.5%Claude Opus 4.1
WeirdML45.9%Not measuredOnly Claude Opus 4.1 measured
Cybench42.0%Not measuredOnly Claude Opus 4.1 measured
ALE-BenchNot measured340.8Only GLM 4.6 measured
LMArena Text: coding14791449Claude Opus 4.1
LMArena Text: software and IT14561455Claude Opus 4.1
LMArena WebDev: HTML13991350Claude Opus 4.1
SciCode4.6%Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Opus 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 4.6Leader
AA Intelligence Index22.818.5Claude Opus 4.1
Epoch Capabilities Index144.1Not measuredOnly Claude Opus 4.1 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Agentic work benchmarks for Claude Opus 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 4.6Leader
Design Arena: agents building full-stack appsNot measured1029Only GLM 4.6 measured
Design Arena: agents building mobile appsNot measured1096Only GLM 4.6 measured
Design Arena: agents building Android appsNot measured1084Only GLM 4.6 measured
Design Arena: agents building Godot gamesNot measured1180Only GLM 4.6 measured
τ²-Bench TelecomNot measured76.9%Only GLM 4.6 measured
METR time horizons66.8%Not measuredOnly Claude Opus 4.1 measured
GDPval43.6%Not measuredOnly Claude Opus 4.1 measured
DeepResearch Bench48.3%Not measuredOnly Claude Opus 4.1 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 31 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for Claude Opus 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 4.6Leader
GPQA Diamond76.3%74.5%Claude Opus 4.1
MMMU Pro (Vals AI)77.5%Not measuredOnly Claude Opus 4.1 measured
GPQA Diamond (Artificial Analysis run)Not measured78.0%Only GLM 4.6 measured
Humanity's Last Exam (Artificial Analysis run)Not measured14.5%Only GLM 4.6 measured
GPQA Diamond (Epoch AI run)77.3%Not measuredOnly Claude Opus 4.1 measured
SimpleBench60.0%Not measuredOnly Claude Opus 4.1 measured
Mystery game puzzles21.0%Not measuredOnly Claude Opus 4.1 measured
EBR-bench7.9%Not measuredOnly Claude Opus 4.1 measured
VPCT35.0%Not measuredOnly Claude Opus 4.1 measured
LMArena Text: hard prompts14421440Claude Opus 4.1
LMArena Text: expert14381432Claude Opus 4.1
LMArena Text: hard prompts in English14511445Claude Opus 4.1
Kagi LLM BenchmarkNot measured45.7%Only GLM 4.6 measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index13
Math benchmarks for Claude Opus 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 4.6Leader
AIME78.2%92.7%GLM 4.6
MATH 500 (Vals AI)95.4%Not measuredOnly Claude Opus 4.1 measured
MGSM (Vals AI)94.4%89.8%Claude Opus 4.1
AA Math IndexNot measured86.0Only GLM 4.6 measured
AIME 2025 (Artificial Analysis run)Not measured86.0%Only GLM 4.6 measured
OTIS Mock AIME68.9%Not measuredOnly Claude Opus 4.1 measured
FrontierMath, tiers 1 to 312.6%Not measuredOnly Claude Opus 4.1 measured
FrontierMath, tier 42.4%Not measuredOnly Claude Opus 4.1 measured
LMArena Text: math14311432GLM 4.6
LMArena Text: mathematical work14341447GLM 4.6
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index44
Knowledge benchmarks for Claude Opus 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 4.6Leader
MMLU Pro87.9%82.2%Claude Opus 4.1
LegalBench (Vals AI)83.5%79.6%Claude Opus 4.1
CorpFin (Vals AI)Not measured56.8%Only GLM 4.6 measured
TaxEval (Vals AI)73.7%66.2%Claude Opus 4.1
MortgageTax (Vals AI)61.1%Not measuredOnly Claude Opus 4.1 measured
MedQA (Vals AI)93.6%92.2%Claude Opus 4.1
MedCode (Vals AI)47.2%Not measuredOnly Claude Opus 4.1 measured
MMLU Pro (Artificial Analysis run)Not measured82.9%Only GLM 4.6 measured
LMArena Text: science14221456GLM 4.6
LMArena Text: medicine and healthcare14161455GLM 4.6
LMArena Text: legal and government14211448GLM 4.6
LMArena Text: business and finance14061416GLM 4.6
FACTS Benchmark Suite40.4%Not measuredOnly Claude Opus 4.1 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 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 4.6Leader
Design Arena: websites11761174Claude Opus 4.1
Design Arena: UI components11621145Claude Opus 4.1
Design Arena: game dev11711150Claude Opus 4.1
Design Arena: data viz11661161Claude Opus 4.1
Design Arena: 3D11521128Claude Opus 4.1
Design Arena: all code categories11701165Claude Opus 4.1
Design Arena: SVG11521108Claude Opus 4.1
Design Arena: ASCII art1167Not measuredOnly Claude Opus 4.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index710
General benchmarks for Claude Opus 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 4.6Leader
SAGE (Vals AI)31.4%Not measuredOnly Claude Opus 4.1 measured
MedScribe (Vals AI)73.9%Not measuredOnly Claude Opus 4.1 measured
IFBenchNot measured43.4%Only GLM 4.6 measured
Long context reasoning (AA-LCR)Not measured54.0%Only GLM 4.6 measured
DTBench80.0%Not measuredOnly Claude Opus 4.1 measured
LMCA37.1%Not measuredOnly Claude Opus 4.1 measured
Creative writing (Lech Mazur)84.7%Not measuredOnly Claude Opus 4.1 measured
LMArena Text14191440GLM 4.6
LMArena Text: instruction following14351410Claude Opus 4.1
LMArena Text: creative writing14121412Claude Opus 4.1
LMArena Text: English14331449GLM 4.6
LMArena Text: non-English14051426GLM 4.6
LMArena Text: Chinese14271499GLM 4.6
LMArena Text: German14131447GLM 4.6
LMArena Text: Japanese13771393GLM 4.6
LMArena Text: Korean13811400GLM 4.6
LMArena Text: French14331459GLM 4.6
LMArena Text: Spanish14481436Claude Opus 4.1
LMArena Text: Russian14221418Claude Opus 4.1
LMArena Text: Polish14131447GLM 4.6
LMArena Text: multi-turn14441427Claude Opus 4.1
LMArena Text: longer queries14551422Claude Opus 4.1
LMArena Text: writing and language14181415Claude Opus 4.1
LMArena Text: entertainment and media13981409GLM 4.6
Neither model has a result on the other 22 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.1 and GLM 4.6
BenchmarkClaude Opus 4.1GLM 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 4.1$0.052Fits 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 4.1$0.975Fits 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 4.1$3.75Exceeds 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 4.1 and GLM 4.6
SpecificationAnthropic Claude Opus 4.1Z.ai GLM 4.6
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedAugust 5, 2025September 30, 2025
Context window200K205K
Input $/Mtok$15.00$0.60
Output $/Mtok$75.00$2.20
Coding indexNot benchmarked8.8
Independent measurements behind it12
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.1 better than GLM 4.6 for coding?

Only GLM 4.6 has a coding score, 8.8 on the Vibe Coding Index; Claude Opus 4.1 has none, so the two cannot be ranked on coding. Pick Claude Opus 4.1 for work measured by LMArena WebDev or Terminal-Bench, where it leads.

Which is cheaper, Claude Opus 4.1 or GLM 4.6?

Claude Opus 4.1 costs $15.00 per million input tokens and $75.00 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 4.1 or GLM 4.6?

GLM 4.6, with 205K tokens against 200K.

How many benchmarks is the Claude Opus 4.1 vs GLM 4.6 comparison based on?

47 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.1's coding index rests on 1 independent benchmark 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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