Claude Fable 5 vs GLM 5.3
Updated October 21, 2026. 92 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Claude Fable 5 for coding: it scores 82.1 on the Vibe Coding Index against 73.1 for GLM 5.3.
Pick GLM 5.3 when output tokens cost 35.7x less, or when a solved task costs $0.36 against $2.16.
- Shared results
- 92
- Claude Fable 5 only
- 34
- GLM 5.3 only
- 8
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Claude Fable 5
Claude Fable 5 scores 82.1 against 73.1.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Claude Fable 5
Claude Fable 5 leads, 49.6 against 44.8.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3
GLM 5.3 leads, 53.1 against 50.7.
Same board, both measured
Reasoning
GPQA Diamond
Claude Fable 5
Claude Fable 5 leads, 93.2% against 88.1%.
Same board, both measured
Knowledge
MMLU Pro
Claude Fable 5
Claude Fable 5 leads, 91.5% against 86.8%.
Same board, both measured
Web design
Design Arena: websites
Claude Fable 5
Claude Fable 5 leads, 1296 against 1295.
Same board, both measured
General
Vals Index
No call
Only GLM 5.3 has a Vals Index result, 59.7%.
Directional only
Long documents
Listed context window
GLM 5.3
GLM 5.3 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3
Claude Fable 5 $0.035, GLM 5.3 $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3
Claude Fable 5 $2.16, GLM 5.3 $0.36.
Published attempt cost and pass rate
At a glance
- Coding index
- Claude Fable 5 82.1 from 2 benchmarks, GLM 5.3 73.1 from 2 benchmarks.
- Widest category
- Math, 23.4 points apart on average over 6 shared benchmarks.
- Widest single gap
- LiveBench browser: Claude Fable 5 92.0% against GLM 5.3 0.0%, 92.0 points apart on a 0 to 100 scale.
- Output price
- Claude Fable 5 $50.00 against GLM 5.3 $1.40 per million output tokens, 35.7x apart.
- Context window
- Claude Fable 5 takes 1M tokens, GLM 5.3 1.05M.
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 5.3 | Ties |
|---|---|---|---|---|
| Coding | 17 | 2 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 11 | 3 | ||
| Reasoning | 9 | 1 | ||
| Math | 6 | 0 | ||
| Knowledge | 8 | 1 | ||
| Web design | 8 | 1 | ||
| General | 21 | 2 | ||
| All shared boards | 82 | 10 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index172
| Benchmark | Claude Fable 5 | GLM 5.3 | Leader |
|---|---|---|---|
| LiveBench coding | 98.3% | 82.8% | Claude Fable 5 |
| LMArena WebDev | 1624 | 1621 | Claude Fable 5 |
| AA Coding Index | 76.5 | 74.8 | Claude Fable 5 |
| LiveCodeBench (Vals AI) | 89.8% | 80.5% | Claude Fable 5 |
| SWE-bench Verified (Vals AI) | 95.0% | 95.4% | GLM 5.3 |
| Terminal-Bench 4 (Vals AI) | 41.4% | 38.9% | Claude Fable 5 |
| Vibe Code Bench (Vals AI) | 90.3% | 78.1% | Claude Fable 5 |
| Code migration (Vals AI) | 55.1% | 44.2% | Claude Fable 5 |
| ProgramBench (Vals AI) | 2.0% | 1.5% | Claude Fable 5 |
| IOI (Vals AI) | Not measured | 68.4% | Only GLM 5.3 measured |
| Terminal-Bench 2.1 (Vals AI) | 80.5% | 71.5% | Claude Fable 5 |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 20.0% | Only GLM 5.3 measured |
| SkillsBench (Vals AI) | Not measured | 47.5% | Only GLM 5.3 measured |
| CyberBench (Vals AI) | Not measured | 72.1% | Only GLM 5.3 measured |
| SciCode | 61.0% | 59.0% | Claude Fable 5 |
| Terminal-Bench Hard (Artificial Analysis run) | 62.9% | Not measured | Only Claude Fable 5 measured |
| FrontierCode | 53.5% | 40.1% | Claude Fable 5 |
| FrontierSWE | 47.0% | 30.2% | Claude Fable 5 |
| GSO-Bench | 78.4% | Not measured | Only Claude Fable 5 measured |
| WeirdML | 91.9% | 75.4% | Claude Fable 5 |
| MirrorCode | 63.9% | Not measured | Only Claude Fable 5 measured |
| ALE-Bench | 2041.3 | 1317.4 | Claude Fable 5 |
| LMArena Text: coding | 1518 | 1497 | Claude Fable 5 |
| LMArena Text: software and IT | 1513 | 1493 | Claude Fable 5 |
| LMArena WebDev: React | 1631 | 1641 | GLM 5.3 |
| LMArena WebDev: HTML | 1651 | 1595 | Claude Fable 5 |
| LMArena WebDev: from an image | 1623 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Fable 5 | GLM 5.3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 49.6 | 44.8 | Claude Fable 5 |
| Epoch Capabilities Index | 163.4 | 156.0 | Claude Fable 5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index113
| Benchmark | Claude Fable 5 | GLM 5.3 | Leader |
|---|---|---|---|
| AA Agentic Index | 50.7 | 53.1 | GLM 5.3 |
| 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 | 1194 | Claude Fable 5 |
| Design Arena: agents building Android apps | 1289 | 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 | 1189 | Claude Fable 5 |
| Design Arena: PowerPoint slides | 1295 | 1255 | Claude Fable 5 |
| LiveBench research | 86.9% | 73.2% | Claude Fable 5 |
| LiveBench browser | 92.0% | 0.0% | Claude Fable 5 |
| LiveBench long agentic | 53.2% | 35.9% | Claude Fable 5 |
| SREBench (Vals AI) | Not measured | 9.2% | Only GLM 5.3 measured |
| Finance Agent (Vals AI) | 56.3% | 55.8% | Claude Fable 5 |
| Tax Agent Bench (Vals AI) | 38.3% | 39.7% | GLM 5.3 |
| Legal Research Bench (Vals AI) | 49.5% | 49.0% | Claude Fable 5 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 14.6% | Only GLM 5.3 measured |
| Excel Modeling Benchmark (Vals AI) | 73.7% | 56.3% | Claude Fable 5 |
| Terminal-Bench-Science (Vals AI) | 15.7% | 5.7% | Claude Fable 5 |
| τ²-Bench Telecom | 98.5% | Not measured | Only Claude Fable 5 measured |
| APEX-Agents | 63.6% | 56.6% | Claude Fable 5 |
| 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 | $8,164 | GLM 5.3 |
| LMArena Search | 1229 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 14 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index91
| Benchmark | Claude Fable 5 | GLM 5.3 | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | 88.1% | Claude Fable 5 |
| LiveBench reasoning | 89.7% | 85.8% | Claude Fable 5 |
| MysteryMechanism (Vals AI) | Not measured | 23.0% | Only GLM 5.3 measured |
| MMMU Pro (Vals AI) | 89.3% | Not measured | Only Claude Fable 5 measured |
| GPQA Diamond (Artificial Analysis run) | 92.6% | 91.7% | Claude Fable 5 |
| Humanity's Last Exam (Artificial Analysis run) | 55.5% | 42.3% | Claude Fable 5 |
| GPQA Diamond (Epoch AI run) | 85.9% | 90.9% | GLM 5.3 |
| 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% | 37.0% | Claude Fable 5 |
| Mystery game puzzles | 52.0% | 33.0% | Claude Fable 5 |
| EBR-bench | 39.5% | Not measured | Only Claude Fable 5 measured |
| LMArena Text: hard prompts | 1507 | 1490 | Claude Fable 5 |
| LMArena Text: expert | 1534 | 1514 | Claude Fable 5 |
| LMArena Text: hard prompts in English | 1509 | 1496 | Claude Fable 5 |
| LMArena Vision: diagrams | 1357 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: homework | 1361 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Fable 5 | GLM 5.3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | 91.1% | Claude Fable 5 |
| FrontierMath, tiers 1 to 3 | 87.0% | 68.8% | Claude Fable 5 |
| FrontierMath, tier 4 | 90.2% | 29.3% | Claude Fable 5 |
| ProofBench | 95.0% | 49.0% | Claude Fable 5 |
| LMArena Text: math | 1516 | 1495 | Claude Fable 5 |
| LMArena Text: mathematical work | 1515 | 1497 | Claude Fable 5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index81
| Benchmark | Claude Fable 5 | GLM 5.3 | Leader |
|---|---|---|---|
| MMLU Pro | 91.5% | 86.8% | Claude Fable 5 |
| LegalBench (Vals AI) | 88.6% | 84.8% | Claude Fable 5 |
| CorpFin (Vals AI) | 71.8% | Not measured | Only Claude Fable 5 measured |
| TaxEval (Vals AI) | 76.9% | 72.4% | Claude Fable 5 |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Claude Fable 5 measured |
| MedCode (Vals AI) | 56.1% | 42.9% | Claude Fable 5 |
| SimpleQA Verified | 70.7% | 41.0% | Claude Fable 5 |
| LMArena Text: science | 1506 | 1498 | Claude Fable 5 |
| LMArena Text: medicine and healthcare | 1480 | 1481 | GLM 5.3 |
| LMArena Text: legal and government | 1498 | 1473 | Claude Fable 5 |
| LMArena Text: business and finance | 1480 | 1459 | Claude Fable 5 |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index81
| Benchmark | Claude Fable 5 | GLM 5.3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1296 | 1295 | Claude Fable 5 |
| Design Arena: UI components | 1318 | 1314 | Claude Fable 5 |
| Design Arena: game dev | 1336 | 1311 | Claude Fable 5 |
| Design Arena: data viz | 1304 | 1260 | Claude Fable 5 |
| Design Arena: 3D | 1319 | 1332 | GLM 5.3 |
| Design Arena: all code categories | 1310 | 1304 | Claude Fable 5 |
| Design Arena: SVG | 1302 | 1292 | Claude Fable 5 |
| Design Arena: ASCII art | 1328 | 1213 | Claude Fable 5 |
| LiveBench design | 84.7% | 77.3% | Claude Fable 5 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index212
| Benchmark | Claude Fable 5 | GLM 5.3 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 59.7% | Only GLM 5.3 measured |
| LiveBench data analysis | 80.5% | 70.2% | Claude Fable 5 |
| Public Benefits Bench (Vals AI) | 70.4% | 68.5% | Claude Fable 5 |
| SAGE (Vals AI) | 51.9% | Not measured | Only Claude Fable 5 measured |
| MedScribe (Vals AI) | 88.5% | 88.8% | GLM 5.3 |
| Vals Multimodal Index | 74.2% | Not measured | Only Claude Fable 5 measured |
| IFBench | 63.5% | Not measured | Only Claude Fable 5 measured |
| Long context reasoning (AA-LCR) | 82.3% | 79.7% | Claude Fable 5 |
| DTBench | 98.4% | 87.7% | Claude Fable 5 |
| LMCA | 61.2% | 55.5% | Claude Fable 5 |
| 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 | 1474 | Claude Fable 5 |
| LMArena Text: instruction following | 1502 | 1479 | Claude Fable 5 |
| LMArena Text: creative writing | 1494 | 1458 | Claude Fable 5 |
| LMArena Vision | 1325 | Not measured | Only Claude Fable 5 measured |
| LMArena Text: English | 1498 | 1482 | Claude Fable 5 |
| LMArena Text: non-English | 1482 | 1459 | Claude Fable 5 |
| LMArena Text: Chinese | 1543 | 1532 | Claude Fable 5 |
| LMArena Text: German | 1486 | 1488 | GLM 5.3 |
| LMArena Text: Japanese | 1504 | 1460 | Claude Fable 5 |
| LMArena Text: Korean | 1487 | 1460 | Claude Fable 5 |
| LMArena Text: French | 1505 | 1503 | Claude Fable 5 |
| LMArena Text: Spanish | 1498 | 1462 | Claude Fable 5 |
| LMArena Text: Russian | 1503 | 1469 | Claude Fable 5 |
| LMArena Text: Polish | 1494 | 1466 | Claude Fable 5 |
| LMArena Text: multi-turn | 1504 | 1472 | Claude Fable 5 |
| LMArena Text: longer queries | 1510 | 1483 | Claude Fable 5 |
| LMArena Text: writing and language | 1501 | 1469 | Claude Fable 5 |
| LMArena Text: entertainment and media | 1482 | 1447 | Claude Fable 5 |
| LMArena Vision: English | 1323 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: Chinese | 1373 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: reading text | 1337 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: humor | 1341 | Not measured | Only Claude Fable 5 measured |
| LMArena Vision: creative writing | 1338 | Not measured | Only Claude Fable 5 measured |
| LMArena Document | 1496 | Not measured | Only Claude Fable 5 measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Fable 5 | GLM 5.3 | 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 5.3 costs less
Repository review
50K input + 3K output tokens
GLM 5.3 costs less
Agent loop
200K input + 10K output tokens
GLM 5.3 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 5.3 |
|---|---|---|
| Maker | Anthropic | Z.ai |
| Weights | No public weights listed | Open weights |
| Released | June 9, 2026 | August 18, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $10.00 | $0.079 |
| Output $/Mtok | $50.00 | $1.40 |
| Coding index | 82.1 | 73.1 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $2.16 | $0.36 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Fable 5 better than GLM 5.3 for coding?
Pick Claude Fable 5 for coding: it scores 82.1 on the Vibe Coding Index against 73.1 for GLM 5.3. Pick GLM 5.3 when output tokens cost 35.7x less, or when a solved task costs $0.36 against $2.16.
Which is cheaper, Claude Fable 5 or GLM 5.3?
Claude Fable 5 costs $10.00 per million input tokens and $50.00 per million output tokens; GLM 5.3 costs $0.079 and $1.40. Per solved SWE-bench Verified task, Claude Fable 5 costs $2.16 and GLM 5.3 $0.36.
Which has the bigger context window, Claude Fable 5 or GLM 5.3?
GLM 5.3, with 1.05M tokens against 1M.
How many benchmarks is the Claude Fable 5 vs GLM 5.3 comparison based on?
92 benchmarks have a result for both models as of October 21, 2026. Claude Fable 5's coding index rests on 2 independent benchmarks and GLM 5.3's on 2. Where only one model has a result, the page says so instead of naming a winner.