Anthropic, proprietary
Claude Fable 5
Claude Fable 5 by Anthropic ranks 5th of 354 ranked models on the Noometry Index as of October 2026, with a score of 66.8. Its strongest category is agentic & tool use, where it ranks 2nd. API pricing starts at $10 per million input tokens and $50 per million output tokens, with a 1M-token context window.
Last verified
Specifications
- Noometry rank
- #5 of 354
- Index score
- 66.8
- Evidence
- Confirmed 62 results
- Provider
- Anthropic
- Released
- June 7, 2026
- Weights
- Proprietary
- Reasoning
- Yes
- Context window
- 1M
- Max output
- 128K
- Input price
- $10 / M
- Output price
- $50 / M
- Blended price
- $20 / M
- Output speed
- 25 tokens/s Kagi
- Value
- #208 of 219
- Knowledge cutoff
- January 2026
- Input
- text, image, pdf
Category scores
Each category score combines every public result we have in that category.
- Coding 70.6
- Agentic & Tool Use 54.0
- Reasoning 76.8
- Math 88.5
- Knowledge 62.2
- Multimodal 45.3
- Multilingual 57.3
- Instruction Following 78.6
- Long Context 46.3
- Writing & Preference 75.9
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 70.6 | #4 | 9 |
| Agentic & Tool Use | 54.0 | #2 | 6 |
| Reasoning | 76.8 | #6 | 14 |
| Math | 88.5 | #5 | 5 |
| Knowledge | 62.2 | #25 | 3 |
| Multimodal | 45.3 | #17 | 3 |
| Multilingual | 57.3 | #9 | 1 |
| Instruction Following | 78.6 | #8 | 1 |
| Long Context | 46.3 | #23 | 1 |
| Writing & Preference | 75.9 | #5 | 5 |
Strengths and weaknesses
Categories where Claude Fable 5 places highest and lowest among the models ranked in each, with its score against that category's median.
Strongest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Coding | 70.6 | +31.9 | #4 of 340, top 2% |
| Agentic & Tool Use | 54.0 | +23.7 | #2 of 154, top 2% |
| Math | 88.5 | +51.9 | #5 of 327, top 2% |
Weakest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Multimodal | 45.3 | +6.7 | #17 of 128, top 14% |
| Knowledge | 62.2 | +24.9 | #25 of 314, top 8% |
| Long Context | 46.3 | +5.4 | #23 of 296, top 8% |
Closest competitors
The models ranked just above and below Claude Fable 5. When scores are this close, price and speed are often the better way to choose.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| GPT-6 Astra | #1 | 70.8 | $20 | — | Compare |
| Claude Fable 5.1 | #2 | 69.0 | $20 | — | Compare |
| Claude Opus 5.5 | #3 | 68.6 | $8 | — | Compare |
| Claude Opus 5 | #4 | 67.8 | $10 | — | Compare |
| GPT-6.1 Sol | #6 | 65.6 | $4 | — | Compare |
| GPT-5.6 Sol | #7 | 65.0 | $8 | 10 | Compare |
| GPT-5.5 Pro | #8 | 64.3 | $67.50 | — | Compare |
| GPT-5.5 | #9 | 63.4 | $11.25 | 25 | Compare |
Sponsored placements are available on pages like this one. Advertise on Noometry
Benchmark results
Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.
Coding
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| DeepSWE | 68.6% | high | Epoch AI | ||
| DeepSWE | 59.6% | low | Epoch AI | ||
| DeepSWE | 69.7% | max | Epoch AI | ||
| DeepSWE | 65.4% | medium | Epoch AI | ||
| DeepSWE | 69.9% | #6 of 29, top 21% | xhigh | Epoch AI | |
| FrontierCode | 53.5% | #2 of 37, top 6% | Epoch AI | ||
| LMArena WebDev | 1625 | #16 of 113, top 15% | high | LMArena | 2026-10-08 |
| FrontierSWE | 47% | #7 of 18, top 39% | max | Epoch AI | |
| SciCode | 61% | #4 of 121, top 4% | max | Epoch AI | |
| GSO | 78.4% | #3 of 31, top 10% | Epoch AI | ||
| WeirdML | 87.8% | high | Epoch AI | ||
| WeirdML | 91.9% | #3 of 119, top 3% | max | Epoch AI | |
| LMArena Coding | 1519 | #7 of 294, top 3% | high | LMArena | 2026-10-08 |
| MirrorCode | 63.9% | #3 of 9, top 34% | high | Epoch AI | 2026-08-10 |
| ALE-Bench | 2,041 | #7 of 105, top 7% | high | Epoch AI |
Agentic & Tool Use
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| APEX-Agents | 63.6% | #10 of 49, top 21% | Epoch AI | ||
| Remote Labor Index | 16.1% | #3 of 14, top 22% | Epoch AI | ||
| τ²-bench Banking | 39.7% | #8 of 26, top 31% | max | τ²-bench | 2026-08-04 |
| PostTrainBench | 41.8% | Best of 11 | max | Epoch AI | |
| GBAEval | 74.5% | #2 of 23, top 9% | Epoch AI | ||
| GDP.pdf | 30% | #5 of 36, top 14% | Epoch AI | ||
| GDP.pdf | 29.8% | max | Epoch AI | ||
| LMArena Search | 1230 | #5 of 32, top 16% | LMArena | 2026-08-24 | |
| Vending-Bench 2 | 4,530 | Epoch AI | |||
| Vending-Bench 2 | 5,680 | #22 of 60, top 37% | high | Epoch AI | |
| Vending-Bench 2 | 5,019 | low | Epoch AI | ||
| Vending-Bench 2 | 4,967 | max | Epoch AI | ||
| Vending-Bench 2 | 4,340 | medium | Epoch AI |
Reasoning
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| FrontierMath (Tiers 1-3) | 87% | #9 of 81, top 12% | max | Epoch AI | 2026-06-09 |
| FrontierMath Tier 4 | 90.2% | #4 of 63, top 7% | max | Epoch AI | 2026-06-09 |
| OTIS Mock AIME 2024-2025 | 100% | Best of 173 | high | Epoch AI | 2026-08-06 |
| OTIS Mock AIME 2024-2025 | 97.8% | low | Epoch AI | 2026-08-06 | |
| OTIS Mock AIME 2024-2025 | 99.7% | max | Epoch AI | 2026-06-10 | |
| ProofBench | 95% | #8 of 77, top 11% | max | Epoch AI | |
| LMArena Math | 1519 | #5 of 285, top 2% | high | LMArena | 2026-10-08 |
| FrontierMath Erdős | 0% | #4 of 7, top 58% | max | Epoch AI | 2026-08-28 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| GPQA Diamond | 83.3% | high | Epoch AI | 2026-08-06 | |
| GPQA Diamond | 78.8% | low | Epoch AI | 2026-08-06 | |
| GPQA Diamond | 85.9% | #61 of 186, top 33% | max | Epoch AI | 2026-08-06 |
| SimpleQA Verified | 70.7% | #6 of 77, top 8% | xhigh | Epoch AI | 2026-08-10 |
| LMArena Expert | 1534 | #8 of 273, top 3% | high | LMArena | 2026-10-08 |
Multimodal
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Vision | 1324 | Best of 122 | high | LMArena | 2026-10-09 |
| Blueprint-Bench 2 | 38.6% | #5 of 31, top 17% | Epoch AI | ||
| Furniture Assembly | 35.8% | #18 of 31, top 59% | max | Epoch AI | 2026-09-10 |
| LMArena Document | 1496 | #4 of 38, top 11% | LMArena | 2026-09-13 |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1481 | #9 of 297, top 4% | high | LMArena | 2026-10-08 |
| LMArena Chinese | 1543 | #8 of 285, top 3% | high | LMArena | 2026-10-08 |
| LMArena French | 1505 | #8 of 223, top 4% | high | LMArena | 2026-10-08 |
| LMArena German | 1486 | #17 of 231, top 8% | high | LMArena | 2026-10-08 |
| LMArena Japanese | 1506 | #5 of 211, top 3% | high | LMArena | 2026-10-08 |
| LMArena Korean | 1488 | #4 of 213, top 2% | high | LMArena | 2026-10-08 |
| LMArena Russian | 1504 | #7 of 283, top 3% | high | LMArena | 2026-10-08 |
| LMArena Spanish | 1498 | #7 of 226, top 4% | high | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Instruction Following | 1502 | #6 of 298, top 3% | high | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Longer Query | 1509 | #6 of 291, top 3% | high | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1491 | #8 of 297, top 3% | high | LMArena | 2026-10-08 |
| LMArena Creative Writing | 1494 | #5 of 295, top 2% | high | LMArena | 2026-10-08 |
| EQ-Bench Creative Writing | 1943 | #10 of 115, top 9% | EQ-Bench | ||
| EQ-Bench 4 | 1340 | #2 of 28, top 8% | EQ-Bench | ||
| LMArena Multi-Turn | 1504 | #4 of 295, top 2% | high | LMArena | 2026-10-08 |
API pricing by provider
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
|---|---|---|---|---|
| anthropic | $10 | $50 | $1 | 2026-10-10 |
| azure | $10 | $50 | $1 | 2026-10-10 |
| bedrock | $10 | $50 | $1 | 2026-10-10 |
| openrouter | $10 | $50 | $1 | 2026-10-10 |
| vertex | $10 | $50 | $1 | 2026-10-10 |
Compare Claude Fable 5
- Claude Fable 5 vs Claude Opus 5
- Claude Fable 5 vs GPT-6.1 Sol
- Claude Fable 5 vs Claude Opus 5.5
- Claude Fable 5 vs GPT-5.6 Sol
- Claude Fable 5 vs Claude Fable 5.1
- Claude Fable 5 vs GPT-5.5 Pro
- Claude Fable 5 vs GPT-6 Astra
- Claude Fable 5 vs Gemini 3.8 Flash
- Claude Fable 5 vs Kimi K3
- Claude Fable 5 vs Grok 4.6
- Claude Fable 5 vs Qwen3.8 Max
- Claude Fable 5 vs GLM-5.3
- Claude Fable 5 vs Muse Spark 1.3
- Claude Fable 5 vs DeepSeek V4 Pro
Other Anthropic models
- Claude Fable 5.169.0
- Claude Opus 5.568.6
- Claude Opus 567.8
- Claude Sonnet 5.561.9
- Claude Opus 4.860.7
- Claude Opus 4.758.3
- Claude Opus 4.658.2
- Claude Sonnet 554.6
Frequently asked questions
How good is Claude Fable 5?
Claude Fable 5 by Anthropic ranks 5th of 354 ranked models on the Noometry Index as of October 2026, with a score of 66.8. Its strongest category is agentic & tool use, where it ranks 2nd. API pricing starts at $10 per million input tokens and $50 per million output tokens, with a 1M-token context window.
How much does Claude Fable 5 cost?
Claude Fable 5 costs $10 per million input tokens and $50 per million output tokens on Anthropic's own API, with cached input at $1.
What is Claude Fable 5's context window?
Claude Fable 5 accepts up to 1M tokens of input and can write up to 128K tokens in one response.
Is Claude Fable 5 open source?
No. Claude Fable 5 is proprietary and available only through Anthropic's API and partner platforms.
How fast is Claude Fable 5?
Claude Fable 5 generated about 25 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.
What are Claude Fable 5's strengths and weaknesses?
Relative to other ranked models, Claude Fable 5 places best in coding, agentic & tool use, math and lowest in multimodal, knowledge, long context.
What is Claude Fable 5 best at?
Its best category is agentic & tool use, where it ranks 2nd on Noometry.