Claude Fable 5 vs GLM 4.6V
Claude Fable 5 leads GLM 4.6V on the Artificial Analysis Intelligence Index, 49.6 to 11.2, and GLM 4.6V costs 55.6x less per output token ($0.90 vs $50.00 per million). Updated October 21, 2026; 34 benchmarks have a result for both.
Claude Fable 5 or GLM 4.6V: which to pick
Only Claude Fable 5 has a coding score, 79.3 on the Vibe Coding Index; GLM 4.6V has none, so the two cannot be ranked on coding.
Pick GLM 4.6V for output tokens 55.6x cheaper ($0.90 vs $50.00 per million).
- Shared results
- 34
- Claude Fable 5 only
- 93
- GLM 4.6V only
- 4
- Like-for-like categories
- 6 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Claude Fable 5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Claude Fable 5
Claude Fable 5 leads, 49.6 against 11.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Claude Fable 5 has a AA Agentic Index result, 50.7.
Directional only
Reasoning
GPQA Diamond
No call
Only Claude Fable 5 has a GPQA Diamond result, 93.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Claude Fable 5 has a MMLU Pro result, 91.5%.
Directional only
Web design
Design Arena: websites
No call
Only Claude Fable 5 has a Design Arena: websites result, 1296.
Directional only
Long documents
Listed context window
Claude Fable 5
Claude Fable 5 takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 4.6V
Claude Fable 5 $0.035, GLM 4.6V $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Claude Fable 5 has the number, $2.16.
Directional only
At a glance
- Coding index
- Claude Fable 5 79.3 from 6 benchmarks, GLM 4.6V not benchmarked.
- Widest category
- Agentic work, 67.0 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Claude Fable 5 98.5% against GLM 4.6V 31.6%, 67.0 points apart on a 0 to 100 scale.
- Output price
- Claude Fable 5 $50.00 against GLM 4.6V $0.90 per million output tokens, 55.6x apart.
- Context window
- Claude Fable 5 takes 1M tokens, GLM 4.6V 131K.
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.
| Category | Claude Fable 5 | Bars | GLM 4.6V | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 7 | 0 | ||
| Knowledge | 4 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 34 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| LiveBench coding | 98.3% | Not measured | Only Claude Fable 5 measured |
| LMArena WebDev | 1624 | Not measured | Only Claude Fable 5 measured |
| AA Coding Index | 76.5 | Not measured | Only Claude Fable 5 measured |
| LiveCodeBench (Vals AI) | 89.8% | Not measured | Only Claude Fable 5 measured |
| SWE-bench Verified (Vals AI) | 95.0% | Not measured | Only Claude Fable 5 measured |
| Terminal-Bench 4 (Vals AI) | 41.4% | Not measured | Only Claude Fable 5 measured |
| Vibe Code Bench (Vals AI) | 90.3% | Not measured | Only Claude Fable 5 measured |
| Code migration (Vals AI) | 55.1% | Not measured | Only Claude Fable 5 measured |
| ProgramBench (Vals AI) | 2.0% | Not measured | Only Claude Fable 5 measured |
| Terminal-Bench 2.1 (Vals AI) | 80.5% | Not measured | Only Claude Fable 5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 41.1% | Only GLM 4.6V measured |
| SciCode | 61.0% | Not measured | Only Claude Fable 5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 62.9% | 14.4% | Claude Fable 5 |
| FrontierCode | 53.5% | Not measured | Only Claude Fable 5 measured |
| FrontierSWE | 47.0% | Not measured | Only Claude Fable 5 measured |
| GSO-Bench | 78.4% | Not measured | Only Claude Fable 5 measured |
| WeirdML | 91.9% | Not measured | Only Claude Fable 5 measured |
| MirrorCode | 63.9% | Not measured | Only Claude Fable 5 measured |
| ALE-Bench | 2041.3 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: coding | 1518 | 1389 | Claude Fable 5 |
| LMArena Text: software and IT | 1513 | 1391 | Claude Fable 5 |
| LMArena WebDev: React | 1631 | Not measured | Only Claude Fable 5 measured |
| LMArena WebDev: HTML | 1651 | Not measured | Only Claude Fable 5 measured |
| LMArena WebDev: from an image | 1623 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| AA Intelligence Index | 49.6 | 11.2 | Claude Fable 5 |
| Epoch Capabilities Index | 163.4 | Not measured | Only Claude Fable 5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| AA Agentic Index | 50.7 | Not measured | Only Claude Fable 5 measured |
| Design Arena: agents building web apps | 1261 | Not measured | Only Claude Fable 5 measured |
| Design Arena: agents building full-stack apps | 1280 | Not measured | Only Claude Fable 5 measured |
| Design Arena: agents building mobile apps | 1264 | Not measured | Only Claude Fable 5 measured |
| Design Arena: agents building Android apps | 1283 | Not measured | Only Claude Fable 5 measured |
| Design Arena: agents building Godot games | 1292 | Not measured | Only Claude Fable 5 measured |
| Design Arena: agents building games | 1285 | Not measured | Only Claude Fable 5 measured |
| Design Arena: HTML slides | 1277 | Not measured | Only Claude Fable 5 measured |
| Design Arena: PowerPoint slides | 1295 | Not measured | Only Claude Fable 5 measured |
| LiveBench research | 86.9% | Not measured | Only Claude Fable 5 measured |
| LiveBench browser | 92.0% | Not measured | Only Claude Fable 5 measured |
| LiveBench long agentic | 53.2% | Not measured | Only Claude Fable 5 measured |
| Finance Agent (Vals AI) | 56.3% | Not measured | Only Claude Fable 5 measured |
| Tax Agent Bench (Vals AI) | 38.3% | Not measured | Only Claude Fable 5 measured |
| Legal Research Bench (Vals AI) | 49.5% | Not measured | Only Claude Fable 5 measured |
| Excel Modeling Benchmark (Vals AI) | 73.7% | Not measured | Only Claude Fable 5 measured |
| Terminal-Bench-Science (Vals AI) | 15.7% | Not measured | Only Claude Fable 5 measured |
| τ²-Bench Telecom | 98.5% | 31.6% | Claude Fable 5 |
| APEX-Agents | 63.6% | Not measured | Only Claude Fable 5 measured |
| Remote Labor Index | 16.1% | Not measured | Only Claude Fable 5 measured |
| PostTrainBench | 41.8% | Not measured | Only Claude Fable 5 measured |
| Vending-Bench 2 | $5,680 | Not measured | Only Claude Fable 5 measured |
| LMArena Search | 1229 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | Not measured | Only Claude Fable 5 measured |
| LiveBench reasoning | 89.7% | Not measured | Only Claude Fable 5 measured |
| MMMU Pro (Vals AI) | 89.3% | Not measured | Only Claude Fable 5 measured |
| GPQA Diamond (Artificial Analysis run) | 92.6% | 71.9% | Claude Fable 5 |
| Humanity's Last Exam (Artificial Analysis run) | 55.5% | 9.6% | Claude Fable 5 |
| GPQA Diamond (Epoch AI run) | 85.9% | Not measured | Only Claude Fable 5 measured |
| ARC-AGI | 98.5% | Not measured | Only Claude Fable 5 measured |
| ARC-AGI-2 | 89.2% | Not measured | Only Claude Fable 5 measured |
| SimpleBench | 81.9% | Not measured | Only Claude Fable 5 measured |
| Chess puzzles | 47.0% | Not measured | Only Claude Fable 5 measured |
| Mystery game puzzles | 52.0% | Not measured | Only Claude Fable 5 measured |
| EBR-bench | 39.5% | Not measured | Only Claude Fable 5 measured |
| LMArena Text: hard prompts | 1507 | 1367 | Claude Fable 5 |
| LMArena Text: expert | 1534 | 1371 | Claude Fable 5 |
| LMArena Text: hard prompts in English | 1509 | 1391 | Claude Fable 5 |
| LMArena Vision: diagrams | 1357 | 1182 | Claude Fable 5 |
| LMArena Vision: homework | 1361 | 1155 | Claude Fable 5 |
| Kagi LLM Benchmark | 91.4% | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 4 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 85.3 | Only GLM 4.6V measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 85.3% | Only GLM 4.6V measured |
| OTIS Mock AIME | 100.0% | Not measured | Only Claude Fable 5 measured |
| FrontierMath, tiers 1 to 3 | 87.0% | Not measured | Only Claude Fable 5 measured |
| FrontierMath, tier 4 | 90.2% | Not measured | Only Claude Fable 5 measured |
| ProofBench | 95.0% | Not measured | Only Claude Fable 5 measured |
| LMArena Text: math | 1516 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: mathematical work | 1515 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| MMLU Pro | 91.5% | Not measured | Only Claude Fable 5 measured |
| LegalBench (Vals AI) | 88.6% | Not measured | Only Claude Fable 5 measured |
| CorpFin (Vals AI) | 71.8% | Not measured | Only Claude Fable 5 measured |
| TaxEval (Vals AI) | 76.9% | Not measured | Only Claude Fable 5 measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Claude Fable 5 measured |
| MedCode (Vals AI) | 56.1% | Not measured | Only Claude Fable 5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 79.9% | Only GLM 4.6V measured |
| SimpleQA Verified | 70.7% | Not measured | Only Claude Fable 5 measured |
| LMArena Text: science | 1506 | 1389 | Claude Fable 5 |
| LMArena Text: medicine and healthcare | 1480 | 1389 | Claude Fable 5 |
| LMArena Text: legal and government | 1498 | 1393 | Claude Fable 5 |
| LMArena Text: business and finance | 1480 | 1359 | Claude Fable 5 |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| Design Arena: websites | 1296 | Not measured | Only Claude Fable 5 measured |
| Design Arena: UI components | 1319 | Not measured | Only Claude Fable 5 measured |
| Design Arena: game dev | 1335 | Not measured | Only Claude Fable 5 measured |
| Design Arena: data viz | 1304 | Not measured | Only Claude Fable 5 measured |
| Design Arena: 3D | 1319 | Not measured | Only Claude Fable 5 measured |
| Design Arena: all code categories | 1310 | Not measured | Only Claude Fable 5 measured |
| Design Arena: SVG | 1302 | Not measured | Only Claude Fable 5 measured |
| Design Arena: ASCII art | 1329 | Not measured | Only Claude Fable 5 measured |
| LiveBench design | 84.7% | Not measured | Only Claude Fable 5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| LiveBench data analysis | 80.5% | Not measured | Only Claude Fable 5 measured |
| Public Benefits Bench (Vals AI) | 70.4% | Not measured | Only Claude Fable 5 measured |
| SAGE (Vals AI) | 51.9% | Not measured | Only Claude Fable 5 measured |
| MedScribe (Vals AI) | 88.5% | Not measured | Only Claude Fable 5 measured |
| Vals Multimodal Index | 74.2% | Not measured | Only Claude Fable 5 measured |
| IFBench | 63.5% | 30.1% | Claude Fable 5 |
| Long context reasoning (AA-LCR) | 82.3% | 48.7% | Claude Fable 5 |
| DTBench | 98.4% | Not measured | Only Claude Fable 5 measured |
| LMCA | 61.2% | Not measured | Only Claude Fable 5 measured |
| Surface Evolver Bench | 95.0% | Not measured | Only Claude Fable 5 measured |
| Furniture assembly | 35.8% | Not measured | Only Claude Fable 5 measured |
| LMArena Text | 1491 | 1376 | Claude Fable 5 |
| LMArena Text: instruction following | 1502 | 1350 | Claude Fable 5 |
| LMArena Text: creative writing | 1494 | 1347 | Claude Fable 5 |
| LMArena Vision | 1325 | 1164 | Claude Fable 5 |
| LMArena Text: English | 1498 | 1395 | Claude Fable 5 |
| LMArena Text: non-English | 1482 | 1358 | Claude Fable 5 |
| LMArena Text: Chinese | 1543 | 1425 | Claude Fable 5 |
| LMArena Text: German | 1486 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Japanese | 1504 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Korean | 1487 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: French | 1505 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Spanish | 1498 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: Russian | 1503 | 1339 | Claude Fable 5 |
| LMArena Text: Polish | 1494 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: multi-turn | 1504 | 1359 | Claude Fable 5 |
| LMArena Text: longer queries | 1510 | 1357 | Claude Fable 5 |
| LMArena Text: writing and language | 1501 | 1347 | Claude Fable 5 |
| LMArena Text: entertainment and media | 1482 | 1343 | Claude Fable 5 |
| LMArena Vision: English | 1323 | 1179 | Claude Fable 5 |
| LMArena Vision: Chinese | 1373 | 1217 | Claude Fable 5 |
| LMArena Vision: reading text | 1337 | 1171 | Claude Fable 5 |
| LMArena Vision: humor | 1341 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: creative writing | 1338 | 1113 | Claude Fable 5 |
| LMArena Document | 1496 | Not measured | Only 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
| Benchmark | Claude Fable 5 | GLM 4.6V | Leader |
|---|---|---|---|
| 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
GLM 4.6V costs less
Repository review
50K input + 3K output tokens
GLM 4.6V costs less
Agent loop
200K input + 10K output tokens
GLM 4.6V 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.
| Specification | Anthropic Claude Fable 5 | Z.ai GLM 4.6V |
|---|---|---|
| Maker | Anthropic | Z.ai |
| Weights | No public weights listed | Open weights |
| Released | June 9, 2026 | December 8, 2025 |
| Context window | 1M | 131K |
| Input $/Mtok | $10.00 | $0.30 |
| Output $/Mtok | $50.00 | $0.90 |
| Coding index | 79.3 | Not benchmarked |
| Independent measurements behind it | 6 | 0 |
| Cost per solved task | $2.16 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Fable 5 better than GLM 4.6V for coding?
Only Claude Fable 5 has a coding score, 79.3 on the Vibe Coding Index; GLM 4.6V has none, so the two cannot be ranked on coding. Pick GLM 4.6V for output tokens 55.6x cheaper ($0.90 vs $50.00 per million).
Which is cheaper, Claude Fable 5 or GLM 4.6V?
Claude Fable 5 costs $10.00 per million input tokens and $50.00 per million output tokens; GLM 4.6V costs $0.30 and $0.90. Cost per solved task is known for Claude Fable 5 only.
Which has the bigger context window, Claude Fable 5 or GLM 4.6V?
Claude Fable 5, with 1M tokens against 131K.
How many benchmarks is the Claude Fable 5 vs GLM 4.6V comparison based on?
34 benchmarks have a result for both models as of October 21, 2026. Claude Fable 5's coding index rests on 6 independent benchmarks and GLM 4.6V's on 0. Where only one model has a result, the page says so instead of naming a winner.