Claude Fable 5.2: Pricing, Context, and Benchmarks
Claude Fable 5.2 is Anthropic's Claude 5 model released on 2026-11-09. It runs on a 1.0M-token context window, priced at $8.00/M input and $40.00/M output. Anthropic model for demanding reasoning and long-horizon agentic work. 1M context, 128K max output; cache hits at 2.5% of input.
Specifications
| Provider | Anthropic |
|---|---|
| Family | Claude 5 |
| Released | 2026-11-09 |
| Status | active |
| Context window | 1.0M tokens |
| Max output | 128K tokens |
| Modalities | text image |
| Capabilities | function calling json mode vision streaming tool use thinking |
| Tokenizer | claude (since Opus 4.7) |
| API endpoint | https://api.anthropic.com/v1/messages |
| Documentation | Official docs ↗ |
| Last updated | 2026-11-14 |
Cost calculator
For 1,000 tokens of input and 1,000 tokens of output per call, this model costs $0.0480 per call. For typical usage:
| Workload | Tokens / call (in/out) | $/call | $/1K calls | $/1M calls |
|---|---|---|---|---|
| Short Q&A | 200 / 100 | $0.005600 | $5.60 | $5,600 |
| Standard chat | 1K / 500 | $0.028000 | $28.00 | $28,000 |
| RAG with retrieval | 4K / 500 | $0.052000 | $52.00 | $52,000 |
| Long doc summary | 20K / 1K | $0.200000 | $200.00 | $200,000 |
| Long context (100K input) | 100K / 2K | $0.860000 | $860.00 | $860,000 |
For more precise estimates including caching discounts, use the LLM API Cost Calculator.
Other Anthropic models
- Claude Haiku 5.5
- Claude Sonnet 5.5
- Claude Opus 5.5
- Claude Opus 4.7
- Claude Sonnet 4.6
- Claude Haiku 4.5
Common comparisons
- Claude Fable 5.2 vs Llama 3.1 405B Side-by-side specs, pricing, and benchmarks
- Claude Fable 5.2 vs Grok 3 Side-by-side specs, pricing, and benchmarks
- Claude Fable 5.2 vs GPT-4o Side-by-side specs, pricing, and benchmarks
- Claude Fable 5.2 vs Command R+ Side-by-side specs, pricing, and benchmarks
API setup
curl https://api.anthropic.com/v1/messages \
-H "Authorization: Bearer $API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "claude-fable-5-2", "messages": [{"role": "user", "content": "Hello"}]}'See the official documentation for the full request/response schema. For pre-flight token counting before paying, use the appropriate token counter.