Claude Fable 5.2
Claude Fable 5.2 is a chat-oriented large language model from Anthropic, tracked here with throughput measurements from Artificial Analysis and provider pricing.
API Pricing
Cheapest input on OpenRouter · cheapest output on OpenRouter| Provider | Input / 1M | Output / 1M | Cached / 1M |
|---|---|---|---|
| $4.00 | $20.00 | $0.100 | |
| $8.00 | $40.00 | $0.200 | |
| $8.00 | $40.00 | $0.200 | |
| $8.00 | $40.00 | $0.200 |
Prices updated daily. Last check: Nov 10, 2026
Compare API pricing for every Claude model →Claude Fable 5.2 pricing by provider
Input, output, and batch rates, plus alternatives, for one provider at a time.
Performance & Benchmarks
Source: Artificial Analysis →Benchmarks measured Nov 2026. Scores are independent evaluations, not vendor-reported.
Model Details
General
- Creator
- Anthropic
- Modalities
- Text
Capabilities
Strengths & Limitations
Strengths
- Measured output throughput of approximately 94.67 tokens per second once generation begins (Artificial Analysis)
- Built by Anthropic, a provider with an established Claude model line and documented API conventions
- Chat-formatted interface, so it drops into existing multi-turn conversational request patterns
- Streaming output at a steady rate suits long-form generation where total completion time matters more than first-token latency
- Throughput and latency figures come from a third-party benchmark source rather than vendor self-reporting
- Listed across providers in our pricing table, allowing direct cost comparison for the same model
Limitations
- Measured time to first token is roughly 253,380 ms (about four minutes), which rules out latency-sensitive interactive use
- Context window size is not confirmed in our database, so maximum input length should be verified with the provider
- Modality support (image, audio, or other non-text input) is not tracked for this model
- No standardized quality benchmark scores (reasoning, coding, or knowledge evaluations) are available in our data for this entry
- Limited published specification detail makes direct feature-by-feature comparison with other Claude models difficult
Key Features
About Claude Fable 5.2
Common Use Cases
Claude Fable 5.2 is best positioned for asynchronous text generation jobs where the long measured time to first token is acceptable: offline document drafting, bulk summarization queues, report generation, content pipelines that run on a schedule, and research or analysis tasks submitted as background jobs. Its roughly 94.67 tokens per second output rate means long responses complete at a reasonable pace once generation starts, which favors workloads that produce substantial text per request rather than many short exchanges. It is a weak fit for live chatbots, autocomplete, voice assistants, or any agent loop that issues many sequential short calls, since the first-token delay would compound on every step. Teams evaluating it should prototype against their own prompts to confirm both quality and end-to-end latency before committing, and should check the pricing table on this page for the providers currently serving it.
Frequently Asked Questions
How much does Claude Fable 5.2 cost?
Pricing varies by provider and by pricing type — input tokens, output tokens, and any cached or batch rates are often billed differently, and providers update rates frequently. See the pricing table on this page for the current figures across the providers we track.
What is Claude Fable 5.2 best used for?
It suits asynchronous, long-form text generation such as batch summarization, document drafting, and scheduled content pipelines. Its measured output rate of about 94.67 tokens per second supports lengthy responses, while the long measured time to first token makes it unsuitable for real-time interactive chat.
Why is the time to first token so high?
Artificial Analysis measured roughly 253,380 ms before the first token appears. A delay of that scale usually reflects extended processing before output is emitted, or provider-side queuing during measurement, rather than ordinary network overhead. Benchmark conditions differ from production, so test against your own provider and prompt mix.
What context window does Claude Fable 5.2 support?
Our database does not carry a confirmed context window for this model. Check Anthropic's documentation or the serving provider's model card for the maximum input length before designing around long-context prompts.
How does it compare to other Anthropic Claude models?
We only hold throughput and latency measurements for Claude Fable 5.2, not standardized quality benchmarks, so a capability-level comparison is not possible from our data alone. On speed, its ~94.67 output tokens per second is competitive, but the measured first-token delay is far higher than typical Claude chat endpoints, which is the main differentiator to account for.