Claude Fable Latest API: toman pricing and code
~anthropic/claude-fable-latest
visiontoolsreasoningjsonfilesYou are billed for the usage the request actually reported. Prices follow the market. Cached input: 72,531 toman / 1M. Web search: 2,901.25 toman / request.Pricing and top-ups
Claude Fable Latest example: reading an image into JSON
The example is picked from this model's own capabilities. Drop in your key and it runs as is.
# tip: a data URI works too — base64 the file and prefix it with data:image/jpeg;base64,
curl https://api.uttapen.ir/v1/chat/completions \
-H "Authorization: Bearer sk-up-…" \
-H "Content-Type: application/json" \
-d '{
"model": "~anthropic/claude-fable-latest",
"messages": [{
"role": "user",
"content": [
{"type": "text", "text": "Return only the invoice number and the total, as JSON."},
{"type": "image_url", "image_url": {"url": "https://example.com/factor.jpg"}}
]
}]
}'import base64, json
from openai import OpenAI
client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")
img = base64.b64encode(open("factor.jpg", "rb").read()).decode()
resp = client.chat.completions.create(
model="~anthropic/claude-fable-latest",
messages=[{
"role": "user",
"content": [
{"type": "text", "text": "Return the invoice number, the date and the total as JSON."},
{"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{img}"}},
],
}],
response_format={"type": "json_object"},
)
print(json.loads(resp.choices[0].message.content))import OpenAI from "openai";
import { readFileSync } from "node:fs";
const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });
const img = readFileSync("factor.jpg").toString("base64");
const resp = await client.chat.completions.create({
model: "~anthropic/claude-fable-latest",
messages: [{
role: "user",
content: [
{ type: "text", text: "Return the invoice number, the date and the total as JSON." },
{ type: "image_url", image_url: { url: `data:image/jpeg;base64,${img}` } },
],
}],
response_format: { type: "json_object" },
});
console.log(JSON.parse(resp.choices[0].message.content));What is Claude Fable Latest good for?
Anthropic publishes this model; we expose it under the id "~anthropic/claude-fable-latest". Its context window is 1,000,000 tokens, roughly 750k English words in one request. A single response can run to 128,000 tokens. On price it sits in the "expensive" band — cheaper than 387 and dearer than 19 of the other paid models in the catalogue.
What it can do beyond plain text: it reads images directly, which makes it a real option for invoices, forms and screenshots; it takes files such as PDFs as input; it supports tool calling, so it can invoke your own functions with valid arguments; it returns schema-valid JSON through response_format, ready to hand to your code; it has a reasoning mode that pays off on multi-step problems, maths and debugging. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper. Keep in mind that reasoning tokens are output tokens and do appear on the bill.
Pricing is 2,901,250 toman per 1M input tokens and 14,506,250 per 1M output tokens. A 1,000-word round trip on Claude Fable Latest lands near 22,630 toman. It supports cached input: repeated context is billed at 72,531 toman per 1M, which matters a lot if your system prompt is long. You are always charged for the usage the request actually reported, never for the estimate, and a failed request costs nothing.
The closest alternative with the same capabilities from a different provider is GPT-6 Astra: Claude Fable Latest works out roughly 1× more expensive, and its context window is smaller. Both run on the same key and the same code, so trying the other one is a single string change.
To make the figure concrete: 100,000 toman of credit buys roughly 4 thousand-word requests on Claude Fable Latest, and every 1,000 toman is about 44 words of round trip. A job with one million input tokens and one million output tokens comes to 17,407,500 toman in total. Filling this model's 1,000,000-token window costs 2,901,250 toman on the input side alone, which is the real reason to keep conversation history short.
Its nearest relative in the catalogue is "anthropic/claude-fable-5", and choosing between those two is where most people hesitate. Both land at nearly the same price on a thousand-word request (22,630 and 22,630 toman). On parameters the other takes tool_choice.
Anthropic has 31 models in our catalogue; the cheapest is Claude 3 Haiku at 566 toman per thousand words and the dearest Claude Opus 4.1 at 33,945. Among the less common parameters it accepts max_completion_tokens, reasoning_effort, verbosity — all through the standard request body. It does not support temperature, tool_choice, top_p, seed, which most models here do, so test before switching if your code relies on them. By context size the nearest option from another provider is Nova 2 Lite at 1,000,000 tokens.
Good fits: work where the quality of the answer matters more than its cost, logic puzzles and code review, pulling text and fields out of images, agents that reach out to APIs and databases, extracting data against a fixed schema, analysing a long document or codebase in one request.
This model always redirects to the latest model in the Claude Fable family.
Three real jobs, priced on this model
Each figure is derived from the prices above and moves when they do.
| Job | Tokens | Cost |
|---|---|---|
| One chat turn with a medium history | 1,500 in + 400 out | 10,154 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 20,309 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 638,275 toman |
Frequently asked
- How do I call Claude Fable Latest from Iran?
- Sign up with your mobile number, top the wallet up in toman, create an API key, then in the official OpenAI SDK point base_url at https://api.uttapen.ir/v1 and set model to "~anthropic/claude-fable-latest". Nothing else in your code changes.
- What does Claude Fable Latest cost in toman?
- 2,901,250 toman per 1M input tokens and 14,506,250 toman per 1M output tokens; a 1,000-word request is around 22,630 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Claude Fable Latest take?
- Up to 1,000,000 tokens per request, roughly 750k words. A single answer can reach 128,000 tokens.
- Does Claude Fable Latest support streaming and tool calling?
- Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Image input is accepted through image_url, as a data URI or a public URL. Structured output through response_format works too.