Model comparison
Claude Fable 5.1 vs GLM-5.3-Flash
Claude Fable 5.1 is the stronger model overall, scoring 69.0 to 51.8 on the Noometry Index. GLM-5.3-Flash costs 84× less per token, which makes it the better buy when Claude Fable 5.1's lead doesn't matter for your workload.
Last verified . 36 shared benchmarks.
Summary
- They share 36 benchmarks with published results for both. Claude Fable 5.1 scores higher in 10 categories and GLM-5.3-Flash in 0 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Fable 5.1 leads 89.6 to 53.3.
- The biggest single-benchmark swing is ProofBench: 100% for Claude Fable 5.1 and 21% for GLM-5.3-Flash.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $10 / $50 for Claude Fable 5.1.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| Claude Fable 5.1 | GLM-5.3-Flash | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 69.0 | 51.8 |
| Released | 2026-09-01 | 2026-08-20 |
| Weights | Proprietary | Open |
| Context window | 1M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $10 | $0.15 |
| Output $ / M tokens | $50 | $0.50 |
| Results tracked | 52 | 40 |
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Category by category
Coding Claude Fable 5.1 leads
Claude Fable 5.1: 74.7 (#1), GLM-5.3-Flash: 53.1 (#31)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| FrontierCode | 50.9% | 31.8% |
| CursorBench | 51.8% | 36.8% |
| LMArena WebDev | 1744 | 1609 |
| FrontierSWE | 56.3% | 18.1% |
| SciCode | 63.1% | 51.6% |
| LMArena Coding | 1528 | 1508 |
| ALE-Bench | 2,143 | 303.55 |
| DeepSWE | — | 63.4% |
| GSO | 88.2% | — |
| WeirdML | 92.9% | — |
| MirrorCode | 73.3% | — |
Agentic & Tool Use Claude Fable 5.1 leads
Claude Fable 5.1: 50.7 (#5), GLM-5.3-Flash: 34.2 (#47)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | 68.6% | 52.8% |
| GDP.pdf | 29.6% | 14% |
| Remote Labor Index | 17.9% | — |
| Vending-Bench 2 | 5,422 | — |
Reasoning Claude Fable 5.1 leads
Claude Fable 5.1: 76.7 (#7), GLM-5.3-Flash: 48.0 (#42)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| ARC-AGI-2 | 90% | 65.8% |
| ARC-AGI-1 | 97.5% | 91% |
| CritPt | 31.1% | 15.4% |
| Chess Puzzles | 47% | 14% |
| LMArena Hard Prompts | 1526 | 1491 |
| Mystery Game Puzzles | 58% | 8% |
| Epoch Capabilities Index | 164.7 | 151.88 |
| NYT Connections (extended) | 90% | — |
| EBR-Bench | 57.1% | — |
| DTBench | 97.6% | — |
| LMCA | 65.5% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
Math Claude Fable 5.1 leads
Claude Fable 5.1: 89.6 (#4), GLM-5.3-Flash: 53.3 (#47)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 90.2% | 55.8% |
| FrontierMath Tier 4 | 87.8% | 17.1% |
| OTIS Mock AIME 2024-2025 | 100% | 93.9% |
| ProofBench | 100% | 21% |
| LMArena Math | 1525 | 1500 |
| FrontierMath Erdős | 0% | — |
Knowledge Claude Fable 5.1 leads
Claude Fable 5.1: 69.6 (#6), GLM-5.3-Flash: 58.4 (#36)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| LMArena Expert | 1535 | 1513 |
| GPQA Diamond | — | 90.2% |
| Humanity's Last Exam | 46.5% | — |
| SimpleQA Verified | 70.8% | — |
Multimodal Claude Fable 5.1 leads
Claude Fable 5.1: 53.9 (#4), GLM-5.3-Flash: 42.8 (#27)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1318 | 1296 |
| Blueprint-Bench 2 | 41.9% | — |
| Furniture Assembly | 70% | — |
| LMArena Document | 1513 | — |
Multilingual Claude Fable 5.1 leads
Claude Fable 5.1: 59.1 (#3), GLM-5.3-Flash: 56.0 (#25)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1507 | 1462 |
| LMArena Chinese | 1586 | 1527 |
| LMArena French | 1525 | 1496 |
| LMArena German | 1500 | 1470 |
| LMArena Japanese | 1543 | 1429 |
| LMArena Korean | 1534 | 1446 |
| LMArena Russian | 1521 | 1469 |
| LMArena Spanish | 1516 | 1471 |
Instruction Following Claude Fable 5.1 leads
Claude Fable 5.1: 79.2 (#6), GLM-5.3-Flash: 77.5 (#20)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1517 | 1478 |
Long Context Claude Fable 5.1 leads
Claude Fable 5.1: 46.7 (#20), GLM-5.3-Flash: 45.4 (#39)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1522 | 1482 |
Writing & Preference Claude Fable 5.1 leads
Claude Fable 5.1: 79.2 (#2), GLM-5.3-Flash: 65.3 (#50)
| Benchmark | Claude Fable 5.1 | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1510 | 1471 |
| LMArena Creative Writing | 1507 | 1442 |
| LMArena Multi-Turn | 1492 | 1467 |
| EQ-Bench Creative Writing | 2162 | — |
Frequently asked questions
Is Claude Fable 5.1 better than GLM-5.3-Flash?
Claude Fable 5.1 is the stronger model overall, scoring 69.0 to 51.8 on the Noometry Index. GLM-5.3-Flash costs 84× less per token, which makes it the better buy when Claude Fable 5.1's lead doesn't matter for your workload.
Which is cheaper, Claude Fable 5.1 or GLM-5.3-Flash?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Claude Fable 5.1 lists at $10 and $50.
Is Claude Fable 5.1 or GLM-5.3-Flash better for coding?
Claude Fable 5.1 scores higher on coding benchmarks: 74.7 versus 53.1 in the Noometry coding category.
Which has the bigger context window?
Both accept 1M tokens.
How many benchmarks do Claude Fable 5.1 and GLM-5.3-Flash share?
36 benchmarks have published results for both models. Claude Fable 5.1 has 52 scored results on Noometry and GLM-5.3-Flash has 40.