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Claude Fable 5 vs GLM 4.6

Claude Fable 5 leads GLM 4.6 on coding, 79.3 to 8.8 on the Vibe Coding Index, and GLM 4.6 costs 22.7x less per output token ($2.20 vs $50.00 per million). Updated October 22, 2026; 58 benchmarks have a result for both.

Claude Fable 5Anthropic
Coding
79.3
Overall
79.0
Output $/M
$50.00
58
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
0
vs boards won of 58 shared

Claude Fable 5 or GLM 4.6: which to pick

Pick Claude Fable 5 for coding: it scores 79.3 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for output tokens 22.7x cheaper ($2.20 vs $50.00 per million).

Shared results
58
Claude Fable 5 only
69
GLM 4.6 only
11
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 Fable 5 79.3 from 6 benchmarks, GLM 4.6 8.8 from 2 benchmarks.
Widest category
Coding, 35.6 points apart on average over 9 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Claude Fable 5 90.3% against GLM 4.6 3.1%, 87.3 points apart on a 0 to 100 scale.
Output price
Claude Fable 5 $50.00 against GLM 4.6 $2.20 per million output tokens, 22.7x apart.
Context window
Claude Fable 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 Fable 5BarsGLM 4.6Ties
Coding90
Intelligence10
Agentic work50
Reasoning70
Math20
Knowledge80
Web design70
General190
All shared boards580
CodingLike-for-likeSix of these boards feed the Vibe Coding Index90
Coding benchmarks for Claude Fable 5 and GLM 4.6
BenchmarkClaude Fable 5GLM 4.6Leader
SWE-bench VerifiedNot measured68.2%Only GLM 4.6 measured
LiveBench coding98.3%Not measuredOnly Claude Fable 5 measured
LMArena WebDev16241341Claude Fable 5
AA Coding Index76.545.8Claude Fable 5
LiveCodeBench (Vals AI)89.8%81.0%Claude Fable 5
SWE-bench Verified (Vals AI)95.0%Not measuredOnly Claude Fable 5 measured
Terminal-Bench 4 (Vals AI)41.4%Not measuredOnly Claude Fable 5 measured
Vibe Code Bench (Vals AI)90.3%3.1%Claude Fable 5
Code migration (Vals AI)55.1%Not measuredOnly Claude Fable 5 measured
ProgramBench (Vals AI)2.0%Not measuredOnly Claude Fable 5 measured
Terminal-Bench 2.1 (Vals AI)80.5%Not measuredOnly Claude Fable 5 measured
LiveCodeBench (Artificial Analysis run)Not measured69.5%Only GLM 4.6 measured
SciCode61.0%Not measuredOnly Claude Fable 5 measured
Terminal-Bench Hard (Artificial Analysis run)62.9%28.8%Claude Fable 5
Terminal-BenchNot measured24.5%Only GLM 4.6 measured
FrontierCode53.5%Not measuredOnly Claude Fable 5 measured
FrontierSWE47.0%Not measuredOnly Claude Fable 5 measured
GSO-Bench78.4%Not measuredOnly Claude Fable 5 measured
WeirdML91.9%Not measuredOnly Claude Fable 5 measured
MirrorCode63.9%Not measuredOnly Claude Fable 5 measured
ALE-Bench2041.3340.8Claude Fable 5
LMArena Text: coding15181449Claude Fable 5
LMArena Text: software and IT15131455Claude Fable 5
LMArena WebDev: React1631Not measuredOnly Claude Fable 5 measured
LMArena WebDev: HTML16511350Claude Fable 5
LMArena WebDev: from an image1623Not measuredOnly Claude Fable 5 measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Claude Fable 5 and GLM 4.6
BenchmarkClaude Fable 5GLM 4.6Leader
AA Intelligence Index49.618.5Claude Fable 5
Epoch Capabilities Index163.4Not measuredOnly Claude Fable 5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index50
Agentic work benchmarks for Claude Fable 5 and GLM 4.6
BenchmarkClaude Fable 5GLM 4.6Leader
AA Agentic Index50.7Not measuredOnly Claude Fable 5 measured
Design Arena: agents building web apps1261Not measuredOnly Claude Fable 5 measured
Design Arena: agents building full-stack apps12801029Claude Fable 5
Design Arena: agents building mobile apps12641096Claude Fable 5
Design Arena: agents building Android apps12841084Claude Fable 5
Design Arena: agents building Godot games12921180Claude Fable 5
Design Arena: agents building games1285Not measuredOnly Claude Fable 5 measured
Design Arena: HTML slides1227Not measuredOnly Claude Fable 5 measured
Design Arena: PowerPoint slides1270Not measuredOnly Claude Fable 5 measured
LiveBench research86.9%Not measuredOnly Claude Fable 5 measured
LiveBench browser92.0%Not measuredOnly Claude Fable 5 measured
LiveBench long agentic53.2%Not measuredOnly Claude Fable 5 measured
Finance Agent (Vals AI)56.3%Not measuredOnly Claude Fable 5 measured
Tax Agent Bench (Vals AI)38.3%Not measuredOnly Claude Fable 5 measured
Legal Research Bench (Vals AI)49.5%Not measuredOnly Claude Fable 5 measured
Excel Modeling Benchmark (Vals AI)73.7%Not measuredOnly Claude Fable 5 measured
Terminal-Bench-Science (Vals AI)15.7%Not measuredOnly Claude Fable 5 measured
τ²-Bench Telecom98.5%76.9%Claude Fable 5
APEX-Agents63.6%Not measuredOnly Claude Fable 5 measured
Remote Labor Index16.1%Not measuredOnly Claude Fable 5 measured
PostTrainBench41.8%Not measuredOnly Claude Fable 5 measured
Vending-Bench 2$5,680Not measuredOnly Claude Fable 5 measured
LMArena Search1229Not measuredOnly Claude Fable 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 16 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for Claude Fable 5 and GLM 4.6
BenchmarkClaude Fable 5GLM 4.6Leader
GPQA Diamond93.2%74.5%Claude Fable 5
LiveBench reasoning89.7%Not measuredOnly Claude Fable 5 measured
MMMU Pro (Vals AI)89.3%Not measuredOnly Claude Fable 5 measured
GPQA Diamond (Artificial Analysis run)92.6%78.0%Claude Fable 5
Humanity's Last Exam (Artificial Analysis run)55.5%14.5%Claude Fable 5
GPQA Diamond (Epoch AI run)85.9%Not measuredOnly Claude Fable 5 measured
ARC-AGI98.5%Not measuredOnly Claude Fable 5 measured
ARC-AGI-289.2%Not measuredOnly Claude Fable 5 measured
SimpleBench81.9%Not measuredOnly Claude Fable 5 measured
Chess puzzles47.0%Not measuredOnly Claude Fable 5 measured
Mystery game puzzles52.0%Not measuredOnly Claude Fable 5 measured
EBR-bench39.5%Not measuredOnly Claude Fable 5 measured
LMArena Text: hard prompts15071440Claude Fable 5
LMArena Text: expert15341432Claude Fable 5
LMArena Text: hard prompts in English15091445Claude Fable 5
LMArena Vision: diagrams1357Not measuredOnly Claude Fable 5 measured
LMArena Vision: homework1361Not measuredOnly Claude Fable 5 measured
Kagi LLM Benchmark91.4%45.7%Claude Fable 5
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Claude Fable 5 and GLM 4.6
BenchmarkClaude Fable 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 Fable 5 measured
FrontierMath, tiers 1 to 387.0%Not measuredOnly Claude Fable 5 measured
FrontierMath, tier 490.2%Not measuredOnly Claude Fable 5 measured
ProofBench95.0%Not measuredOnly Claude Fable 5 measured
LMArena Text: math15161432Claude Fable 5
LMArena Text: mathematical work15151447Claude Fable 5
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
Knowledge benchmarks for Claude Fable 5 and GLM 4.6
BenchmarkClaude Fable 5GLM 4.6Leader
MMLU Pro91.5%82.2%Claude Fable 5
LegalBench (Vals AI)88.6%79.6%Claude Fable 5
CorpFin (Vals AI)71.8%56.8%Claude Fable 5
TaxEval (Vals AI)76.9%66.2%Claude Fable 5
MortgageTax (Vals AI)68.9%Not measuredOnly Claude Fable 5 measured
MedQA (Vals AI)Not measured92.2%Only GLM 4.6 measured
MedCode (Vals AI)56.1%Not measuredOnly Claude Fable 5 measured
MMLU Pro (Artificial Analysis run)Not measured82.9%Only GLM 4.6 measured
SimpleQA Verified70.7%Not measuredOnly Claude Fable 5 measured
LMArena Text: science15061456Claude Fable 5
LMArena Text: medicine and healthcare14801455Claude Fable 5
LMArena Text: legal and government14981448Claude Fable 5
LMArena Text: business and finance14801416Claude Fable 5
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 Fable 5 and GLM 4.6
BenchmarkClaude Fable 5GLM 4.6Leader
Design Arena: websites12951174Claude Fable 5
Design Arena: UI components13161145Claude Fable 5
Design Arena: game dev13351150Claude Fable 5
Design Arena: data viz13041161Claude Fable 5
Design Arena: 3D13181128Claude Fable 5
Design Arena: all code categories13101165Claude Fable 5
Design Arena: SVG13021108Claude Fable 5
Design Arena: ASCII art1329Not measuredOnly Claude Fable 5 measured
LiveBench design84.7%Not measuredOnly Claude Fable 5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for Claude Fable 5 and GLM 4.6
BenchmarkClaude Fable 5GLM 4.6Leader
LiveBench data analysis80.5%Not measuredOnly Claude Fable 5 measured
Public Benefits Bench (Vals AI)70.4%Not measuredOnly Claude Fable 5 measured
SAGE (Vals AI)51.9%Not measuredOnly Claude Fable 5 measured
MedScribe (Vals AI)88.5%Not measuredOnly Claude Fable 5 measured
Vals Multimodal Index74.2%Not measuredOnly Claude Fable 5 measured
IFBench63.5%43.4%Claude Fable 5
Long context reasoning (AA-LCR)82.3%54.0%Claude Fable 5
DTBench98.4%Not measuredOnly Claude Fable 5 measured
LMCA61.2%Not measuredOnly Claude Fable 5 measured
Surface Evolver Bench95.0%Not measuredOnly Claude Fable 5 measured
Furniture assembly35.8%Not measuredOnly Claude Fable 5 measured
LMArena Text14911440Claude Fable 5
LMArena Text: instruction following15021410Claude Fable 5
LMArena Text: creative writing14941412Claude Fable 5
LMArena Vision1325Not measuredOnly Claude Fable 5 measured
LMArena Text: English14981449Claude Fable 5
LMArena Text: non-English14821426Claude Fable 5
LMArena Text: Chinese15431499Claude Fable 5
LMArena Text: German14861447Claude Fable 5
LMArena Text: Japanese15041393Claude Fable 5
LMArena Text: Korean14871400Claude Fable 5
LMArena Text: French15051459Claude Fable 5
LMArena Text: Spanish14981436Claude Fable 5
LMArena Text: Russian15031418Claude Fable 5
LMArena Text: Polish14941447Claude Fable 5
LMArena Text: multi-turn15041427Claude Fable 5
LMArena Text: longer queries15101422Claude Fable 5
LMArena Text: writing and language15011415Claude Fable 5
LMArena Text: entertainment and media14821409Claude Fable 5
LMArena Vision: English1323Not measuredOnly Claude Fable 5 measured
LMArena Vision: Chinese1373Not measuredOnly Claude Fable 5 measured
LMArena Vision: reading text1337Not measuredOnly Claude Fable 5 measured
LMArena Vision: humor1341Not measuredOnly Claude Fable 5 measured
LMArena Vision: creative writing1338Not measuredOnly Claude Fable 5 measured
LMArena Document1496Not measuredOnly Claude Fable 5 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Fable 5 and GLM 4.6
BenchmarkClaude Fable 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 Fable 5$0.035Fits in one request
GLM 4.6$0.0017Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

Claude Fable 5$0.650Fits in one request
GLM 4.6$0.037Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

Claude Fable 5$2.50Fits 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 Fable 5 and GLM 4.6
SpecificationAnthropic Claude Fable 5Z.ai GLM 4.6
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedJune 9, 2026September 30, 2025
Context window1M205K
Input $/Mtok$10.00$0.60
Output $/Mtok$50.00$2.20
Coding index79.38.8
Independent measurements behind it62
Cost per solved task$2.16Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Fable 5 better than GLM 4.6 for coding?

Pick Claude Fable 5 for coding: it scores 79.3 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for output tokens 22.7x cheaper ($2.20 vs $50.00 per million).

Which is cheaper, Claude Fable 5 or GLM 4.6?

Claude Fable 5 costs $10.00 per million input tokens and $50.00 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for Claude Fable 5 only.

Which has the bigger context window, Claude Fable 5 or GLM 4.6?

Claude Fable 5, with 1M tokens against 205K.

How many benchmarks is the Claude Fable 5 vs GLM 4.6 comparison based on?

58 benchmarks have a result for both models as of October 22, 2026. Claude Fable 5's coding index rests on 6 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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