Claude 3 Haiku API: toman pricing and code
anthropic/claude-3-haiku
visiontoolsYou are billed for the usage the request actually reported. Prices follow the market. Cached input: 8,704 toman / 1M. Web search: 2,901.25 toman / request.Pricing and top-ups
Claude 3 Haiku 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-3-haiku",
"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-3-haiku",
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-3-haiku",
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 3 Haiku good for?
Claude 3 Haiku is one of Anthropic's models. Put "anthropic/claude-3-haiku" in the model field and the rest of your code stays as it is. Claude 3 Haiku keeps 200,000 tokens in view at once, and that number is what caps the conversation history in your product. A single response can run to 4,096 tokens. On price it sits in the "cheap" band — cheaper than 164 and dearer than 242 of the other paid models in the catalogue.
Capabilities available on this id: it reads images directly, which makes it a real option for invoices, forms and screenshots; it supports tool calling, so it can invoke your own functions with valid arguments. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper.
For a back-of-envelope figure: about 566 toman per 1,000-word exchange (72,531 in, 362,656 out, per 1M tokens). It supports cached input: repeated context is billed at 8,704 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 Gemini 2.5 Flash (batch): Claude 3 Haiku works out roughly 1.1× 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 177 thousand-word requests on Claude 3 Haiku, and every 1,000 toman is about 1,767 words of round trip. A job with one million input tokens and one million output tokens comes to 435,188 toman in total. Filling this model's 200,000-token window costs 14,506 toman on the input side alone, which is the real reason to keep conversation history short.
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 top_k — all through the standard request body. It does not support include_reasoning, reasoning, response_format, 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 o1 at 200,000 tokens.
What to use it for: high-volume work such as classification, tagging and bulk summarising, pulling text and fields out of images, agents that reach out to APIs and databases, analysing a long document or codebase in one request.
Claude 3 Haiku is Anthropic's fastest and most compact model for near-instant responsiveness. Quick and accurate targeted performance. See the launch announcement and benchmark results [here](https://www.anthropic.com/news/claude-3-haiku) #multimodal
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 | 254 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 508 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 15,957 toman |
Frequently asked
- How do I call Claude 3 Haiku 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-3-haiku". Nothing else in your code changes.
- What does Claude 3 Haiku cost in toman?
- 72,531 toman per 1M input tokens and 362,656 toman per 1M output tokens; a 1,000-word request is around 566 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Claude 3 Haiku take?
- Up to 200,000 tokens per request, roughly 150k words. A single answer can reach 4,096 tokens.
- Does Claude 3 Haiku 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.