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anthropic/claude-fable-5-1Claude's deepest reasoning, for the hardest cases
Claude Fable 5.1 is the model Anthropic reserves for demanding reasoning and long-horizon agentic work, or for cases where Opus 5.5 at higher effort still falls short. It holds a 1M-token context and always thinks before it answers.
According to Anthropic, it improves on long-session agentic coding, multistep research and work on documents, spreadsheets and slides. It also reads dense charts and tables nested in PDFs.
Through Tchavi you use it with mobile money, no card and no KYC, with the same API key as 100+ models. Try Opus 5.5 first: if Fable makes the difference, just change the model field.
The model Anthropic reserves for its most demanding tasks
Reasons over the whole window and connects distant details
Agentic coding, refactors and migrations over multi-hour sessions
From a first question to a finished document, sheet or slide deck
Breaks a question down, gathers evidence and reconciles it
Reads dense charts, filings and tables inside PDFs
Audit this codebase for security issues, verify each finding against the actual code path, and drop anything you cannot prove is reachable. End with a table of severity, file, evidence.
Reconcile these four quarterly spreadsheets, explain every discrepancy over 1%, and tell me which figures I should not trust and why.
Start with Opus 5.5, as Anthropic recommends. Move to Fable 5.1 for the most demanding reasoning and very long agentic runs, or when your tests on Opus 5.5 at high effort still fall short.
Anthropic places Fable 5.1 above the Opus line. Opus 5 stays an option if your code forces a specific tool or turns thinking off, two things Fable 5.1 rejects.
1M tokens in and up to 128K out, with images and PDFs in the same request.
Fable 5.1 rejects tool_choice "any" or a named tool (400 error). Keep "auto" and say in the prompt when to use the tool: Anthropic says it follows explicit instructions reliably.
With the OpenAI SDK, change the base URL, use your sk-tch-… key and model: "claude-fable-5-1" on /v1/chat/completions. The Anthropic-format /v1/messages endpoint works too.
Yes. Top up your Tchavi account with Orange Money, MTN MoMo, M-Pesa or another mobile money operator. No bank card is needed. Credits land as soon as the payment is confirmed and are deducted as you use them.
Yes. Keep your current OpenAI SDK, just change the base URL to Tchavi's (shown in the API tab) and use your Tchavi key. The rest of your code stays the same.
import Tchavi from '@tchavi/sdk';
const client = new Tchavi({ apiKey: 'API_KEY' });
const response = await client.chat.completions.create({
model: 'claude-fable-5-1',
messages: [
{
"role": "user",
"content": "Hello!"
}
],
});
console.log(response.choices[0].message.content);
console.log('Credits used:', response.tchavi.credits_used);Every parameter this model accepts on the API. Check the SDK for full typings.
modelRequiredID of the chat model (e.g. `claude-fable-5-1`).
messagesRequiredConversation messages. Each item has a `role` (system/user/assistant) and a `content` that's either a plain string or an array of content blocks (`text`, `image_url`, `document_url`).
temperature1Sampling temperature between 0 and 2. Higher values = more random.
max_tokensMaximum number of tokens to generate in the response.
streamfalseIf true, partial message deltas are streamed as Server-Sent Events.
toolsFunction-calling toolbox. Pass an array of `{ type: "function", function: { name, description, parameters } }`. Returned tool calls land in `choices[].message.tool_calls`. Only models with `supportsTools: true` accept this.
tool_choiceHow the model picks among tools: `"auto"` (default), `"none"` to force a plain text reply, or `{ type: "function", function: { name } }` to force a specific tool. Only with `supportsTools: true`.
top_p1Nucleus sampling: only tokens in the top `top_p` probability mass are considered.
stopUp to 4 sequences where the API will stop generating further tokens.
frequency_penalty0Between -2.0 and 2.0. Positive values penalize tokens that have appeared frequently.
presence_penalty0Between -2.0 and 2.0. Positive values encourage the model to talk about new topics.
messages[].content[].image_urlAttach an image on a user message. Pass a content block `{ "type": "image_url", "image_url": { "url": ... } }`. PNG / JPEG / WebP, up to 4 per request. Only models with `supportsImageInput: true` accept this block (e.g. `gpt-4o`, `claude-opus-4-7`).
messages[].content[].document_urlAttach a PDF on a user message. Pass a content block `{ "type": "document_url", "document_url": { "url": ... } }`. Up to 5 PDFs per request. Only models with `supportsDocuments: true` accept this block (e.g. `claude-sonnet-4-6`, `gpt-4.1`).
effort"high"Reasoning depth on Anthropic adaptive-thinking models (Opus 4.7+ / Sonnet 4.6+). Values `"low"`, `"medium"`, `"high"`. Higher = more deliberate, slower. Defaults to `"high"` on Opus 4.8.
Estimated over 30 days, for a typical message: ~500 input + ~150 output tokens, billed to the thousandth of a credit.