Model comparison
Claude Fable 5 vs GLM-5.2
Claude Fable 5 is the stronger model overall, scoring 66.8 to 51.1 on the Noometry Index. GLM-5.2 costs 9.3× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Last verified . 49 shared benchmarks.
Summary
- They share 49 benchmarks with published results for both. Claude Fable 5 scores higher in 9 categories and GLM-5.2 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Fable 5 leads 76.8 to 42.3.
- The biggest single-benchmark swing is GBAEval: 74.5% for Claude Fable 5 and 0% for GLM-5.2.
- GLM-5.2 is cheaper at $1.40 / $4.40 per million input/output tokens, against $10 / $50 for Claude Fable 5.
- GLM-5.2 has downloadable open weights; the other is API-only.
Side by side
| Claude Fable 5 | GLM-5.2 | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 66.8 | 51.1 |
| Released | 2026-06-07 | 2026-06-13 |
| Weights | Proprietary | Open |
| Context window | 1M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $10 | $1.40 |
| Output $ / M tokens | $50 | $4.40 |
| Results tracked | 62 | 51 |
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Category by category
Coding Claude Fable 5 leads
Claude Fable 5: 70.6 (#4), GLM-5.2: 51.3 (#41)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| DeepSWE | 69.9% | 43.8% |
| FrontierCode | 53.5% | 24.5% |
| LMArena WebDev | 1625 | 1603 |
| SciCode | 61% | 50.5% |
| WeirdML | 91.9% | 70.1% |
| LMArena Coding | 1519 | 1485 |
| ALE-Bench | 2,041 | 1,047 |
| SWE-bench Verified | — | 78.7% |
| FrontierSWE | 47% | — |
| GSO | 78.4% | — |
| MirrorCode | 63.9% | — |
Agentic & Tool Use Claude Fable 5 leads
Claude Fable 5: 54.0 (#2), GLM-5.2: 32.4 (#63)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| APEX-Agents | 63.6% | 45.2% |
| τ²-bench Banking | 39.7% | 37.1% |
| PostTrainBench | 41.8% | 31.7% |
| GBAEval | 74.5% | 0% |
| Vending-Bench 2 | 5,680 | 8,314 |
| Remote Labor Index | 16.1% | — |
| GDP.pdf | 30% | — |
| LMArena Search | 1230 | — |
Reasoning Claude Fable 5 leads
Claude Fable 5: 76.8 (#6), GLM-5.2: 42.3 (#52)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| ARC-AGI-2 | 89.2% | 22.8% |
| SimpleBench | 81.9% | 58.8% |
| Kagi LLM Benchmark | 91.4% | 62.6% |
| NYT Connections (extended) | 92.7% | 74.3% |
| ARC-AGI-1 | 98.5% | 77% |
| CritPt | 28.6% | 20.9% |
| Chess Puzzles | 41% | 21% |
| EBR-Bench | 39.5% | 9.5% |
| LMArena Hard Prompts | 1508 | 1480 |
| Mystery Game Puzzles | 52% | 19% |
| DTBench | 98.4% | 93.6% |
| LMCA | 61.1% | 45.8% |
| Surface Evolver Bench | 95% | 55.6% |
| Epoch Capabilities Index | 162.06 | 151.78 |
| EnigmaEval | 39.3% | — |
| Bench to the Future 3 | 0.13 | — |
Math Claude Fable 5 leads
Claude Fable 5: 88.5 (#5), GLM-5.2: 55.7 (#43)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 87% | 59.2% |
| FrontierMath Tier 4 | 90.2% | 29.3% |
| OTIS Mock AIME 2024-2025 | 100% | 86.4% |
| ProofBench | 95% | 35% |
| LMArena Math | 1519 | 1482 |
| MathArena Final-Answer Competitions | — | 67.6% |
| FrontierMath Erdős | 0% | — |
Knowledge Claude Fable 5 leads
Claude Fable 5: 62.2 (#25), GLM-5.2: 57.1 (#40)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| GPQA Diamond | 85.9% | 91.9% |
| SimpleQA Verified | 70.7% | 34.2% |
| LMArena Expert | 1534 | 1486 |
Multimodal Not comparable
Claude Fable 5: 45.3 (#17), GLM-5.2: —
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| LMArena Vision | 1324 | — |
| Blueprint-Bench 2 | 38.6% | — |
| Furniture Assembly | 35.8% | — |
| LMArena Document | 1496 | — |
Multilingual Claude Fable 5 leads
Claude Fable 5: 57.3 (#9), GLM-5.2: 55.8 (#26)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| LMArena Non-English | 1481 | 1459 |
| LMArena Chinese | 1543 | 1519 |
| LMArena French | 1505 | 1479 |
| LMArena German | 1486 | 1468 |
| LMArena Japanese | 1506 | 1451 |
| LMArena Korean | 1488 | 1445 |
| LMArena Russian | 1504 | 1466 |
| LMArena Spanish | 1498 | 1477 |
Instruction Following Claude Fable 5 leads
Claude Fable 5: 78.6 (#8), GLM-5.2: 76.9 (#34)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| LMArena Instruction Following | 1502 | 1465 |
Long Context Claude Fable 5 leads
Claude Fable 5: 46.3 (#23), GLM-5.2: 45.3 (#43)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| LMArena Longer Query | 1509 | 1479 |
Writing & Preference Claude Fable 5 leads
Claude Fable 5: 75.9 (#5), GLM-5.2: 70.4 (#21)
| Benchmark | Claude Fable 5 | GLM-5.2 |
|---|---|---|
| LMArena Text | 1491 | 1470 |
| LMArena Creative Writing | 1494 | 1462 |
| EQ-Bench Creative Writing | 1943 | 1757 |
| EQ-Bench 4 | 1340 | 1222 |
| LMArena Multi-Turn | 1504 | 1469 |
Frequently asked questions
Is Claude Fable 5 better than GLM-5.2?
Claude Fable 5 is the stronger model overall, scoring 66.8 to 51.1 on the Noometry Index. GLM-5.2 costs 9.3× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Which is cheaper, Claude Fable 5 or GLM-5.2?
GLM-5.2 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Claude Fable 5 lists at $10 and $50.
Is Claude Fable 5 or GLM-5.2 better for coding?
Claude Fable 5 scores higher on coding benchmarks: 70.6 versus 51.3 in the Noometry coding category.
Which has the bigger context window?
Both accept 1M tokens.
How many benchmarks do Claude Fable 5 and GLM-5.2 share?
49 benchmarks have published results for both models. Claude Fable 5 has 62 scored results on Noometry and GLM-5.2 has 51.