Model comparison
Claude Fable 5 vs GPT-5.6 Terra
Claude Fable 5 is the stronger model overall, scoring 66.8 to 59.2 on the Noometry Index. GPT-5.6 Terra costs 4.4× less per token, which makes it the better buy when Claude Fable 5's lead doesn't matter for your workload.
Last verified . 50 shared benchmarks.
Summary
- They share 50 benchmarks with published results for both. Claude Fable 5 scores higher in 9 categories and GPT-5.6 Terra in 1 category; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Fable 5 leads 76.8 to 60.7.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 91.4% for Claude Fable 5 and 51.3% for GPT-5.6 Terra.
- GPT-5.6 Terra is cheaper at $2 / $12 per million input/output tokens, against $10 / $50 for Claude Fable 5.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 1M.
Side by side
| Claude Fable 5 | GPT-5.6 Terra | |
|---|---|---|
| Provider | Anthropic | OpenAI |
| Noometry Index | 66.8 | 59.2 |
| Released | 2026-06-07 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $10 | $2 |
| Output $ / M tokens | $50 | $12 |
| Results tracked | 62 | 52 |
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Category by category
Coding Claude Fable 5 leads
Claude Fable 5: 70.6 (#4), GPT-5.6 Terra: 57.7 (#19)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| DeepSWE | 69.9% | 69.6% |
| FrontierCode | 53.5% | 41.3% |
| LMArena WebDev | 1625 | 1522 |
| SciCode | 61% | 55% |
| WeirdML | 91.9% | 78.3% |
| LMArena Coding | 1519 | 1484 |
| ALE-Bench | 2,041 | 1,951 |
| CursorBench | — | 41.3% |
| FrontierSWE | 47% | — |
| GSO | 78.4% | — |
| MirrorCode | 63.9% | — |
Agentic & Tool Use Claude Fable 5 leads
Claude Fable 5: 54.0 (#2), GPT-5.6 Terra: 40.1 (#25)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| APEX-Agents | 63.6% | 58.2% |
| GDP.pdf | 30% | 24.7% |
| Vending-Bench 2 | 5,680 | 7,343 |
| Remote Labor Index | 16.1% | — |
| τ²-bench Banking | 39.7% | — |
| PostTrainBench | 41.8% | — |
| BALROG | — | 53.2% |
| GBAEval | 74.5% | — |
| LMArena Search | 1230 | — |
Reasoning Claude Fable 5 leads
Claude Fable 5: 76.8 (#6), GPT-5.6 Terra: 60.7 (#21)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| ARC-AGI-2 | 89.2% | 83.9% |
| SimpleBench | 81.9% | 48.9% |
| Kagi LLM Benchmark | 91.4% | 51.3% |
| NYT Connections (extended) | 92.7% | 78.4% |
| ARC-AGI-1 | 98.5% | 96.5% |
| CritPt | 28.6% | 30% |
| Chess Puzzles | 41% | 54% |
| LMArena Hard Prompts | 1508 | 1468 |
| Mystery Game Puzzles | 52% | 35% |
| DTBench | 98.4% | 93.3% |
| LMCA | 61.1% | 55% |
| Surface Evolver Bench | 95% | 83.8% |
| Epoch Capabilities Index | 162.06 | 159.62 |
| EnigmaEval | 39.3% | — |
| EBR-Bench | 39.5% | — |
| Bench to the Future 3 | 0.13 | — |
Math Claude Fable 5 leads
Claude Fable 5: 88.5 (#5), GPT-5.6 Terra: 81.6 (#12)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 87% | 86% |
| FrontierMath Tier 4 | 90.2% | 70.7% |
| OTIS Mock AIME 2024-2025 | 100% | 99.7% |
| ProofBench | 95% | 74% |
| LMArena Math | 1519 | 1466 |
| FrontierMath Erdős | 0% | — |
Knowledge Claude Fable 5 leads
Claude Fable 5: 62.2 (#25), GPT-5.6 Terra: 61.2 (#30)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| GPQA Diamond | 85.9% | 93.3% |
| SimpleQA Verified | 70.7% | 43.2% |
| LMArena Expert | 1534 | 1492 |
Multimodal GPT-5.6 Terra leads
Claude Fable 5: 45.3 (#17), GPT-5.6 Terra: 47.3 (#11)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | 1324 | 1271 |
| Blueprint-Bench 2 | 38.6% | 30.8% |
| Furniture Assembly | 35.8% | 54.2% |
| LMArena Document | 1496 | 1472 |
Multilingual Claude Fable 5 leads
Claude Fable 5: 57.3 (#9), GPT-5.6 Terra: 54.4 (#44)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | 1481 | 1439 |
| LMArena Chinese | 1543 | 1513 |
| LMArena French | 1505 | 1471 |
| LMArena German | 1486 | 1460 |
| LMArena Japanese | 1506 | 1457 |
| LMArena Korean | 1488 | 1425 |
| LMArena Russian | 1504 | 1450 |
| LMArena Spanish | 1498 | 1448 |
Instruction Following Claude Fable 5 leads
Claude Fable 5: 78.6 (#8), GPT-5.6 Terra: 76.4 (#40)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | 1502 | 1454 |
Long Context Claude Fable 5 leads
Claude Fable 5: 46.3 (#23), GPT-5.6 Terra: 44.4 (#68)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | 1509 | 1451 |
Writing & Preference Claude Fable 5 leads
Claude Fable 5: 75.9 (#5), GPT-5.6 Terra: 70.2 (#23)
| Benchmark | Claude Fable 5 | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | 1491 | 1447 |
| LMArena Creative Writing | 1494 | 1410 |
| EQ-Bench Creative Writing | 1943 | 1855 |
| EQ-Bench 4 | 1340 | 1234 |
| LMArena Multi-Turn | 1504 | 1449 |
Frequently asked questions
Is Claude Fable 5 better than GPT-5.6 Terra?
Claude Fable 5 is the stronger model overall, scoring 66.8 to 59.2 on the Noometry Index. GPT-5.6 Terra costs 4.4× 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 GPT-5.6 Terra?
GPT-5.6 Terra is cheaper. It lists at $2 per million input tokens and $12 per million output tokens; Claude Fable 5 lists at $10 and $50.
Is Claude Fable 5 or GPT-5.6 Terra better for coding?
Claude Fable 5 scores higher on coding benchmarks: 70.6 versus 57.7 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Terra does, with 1.05M tokens against 1M.
How many benchmarks do Claude Fable 5 and GPT-5.6 Terra share?
50 benchmarks have published results for both models. Claude Fable 5 has 62 scored results on Noometry and GPT-5.6 Terra has 52.