Claude Haiku 4.5 API: toman pricing and code
anthropic/claude-haiku-4.5
visiontoolsreasoningjsonfilesYou are billed for the usage the request actually reported. Prices follow the market. Cached input: 29,013 toman / 1M. Web search: 2,901.25 toman / request.Pricing and top-ups
Claude Haiku 4.5 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-haiku-4.5",
"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-haiku-4.5",
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-haiku-4.5",
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 Haiku 4.5 good for?
Claude Haiku 4.5 is one of Anthropic's models. Put "anthropic/claude-haiku-4.5" in the model field and the rest of your code stays as it is. Claude Haiku 4.5 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 64,000 tokens. On price it sits in the "mid-range" band — cheaper than 287 and dearer than 119 of the other paid models in the catalogue.
What you get on top of text in, text out: 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.
Input runs at 290,125 toman per 1M tokens and output at 1,450,625 — output costs 5× input, so trimming the answer saves more than trimming the prompt. It supports cached input: repeated context is billed at 29,013 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 Pro (batch): Claude Haiku 4.5 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 44 thousand-word requests on Claude Haiku 4.5, and every 1,000 toman is about 442 words of round trip. A job with one million input tokens and one million output tokens comes to 1,740,750 toman in total. Filling this model's 200,000-token window costs 58,025 toman on the input side alone, which is the real reason to keep conversation history short.
This id gets confused with "anthropic/claude-haiku-4.5:batch", because the underlying model is the same. The difference is the suffix: no suffix (the standard variant) against "batch". On a thousand-word request this variant works out 2× dearer (2,263 against 1,131 toman). On parameters, this one takes max_completion_tokens.
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, top_k — all through the standard request body. It does not support 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.
Where it makes sense: product chatbots and internal assistants, where cost and quality have to balance, 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.
Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...
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 | 1,015 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 2,031 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 63,828 toman |
Other variants of this model
Same core model, different execution terms and different price. This page is the standard variant.
| Variant | Model id | Output / 1M | Context |
|---|---|---|---|
| batch (cheaper, slower) | anthropic/claude-haiku-4.5:batch | 725,313 | 200,000 |
Put the variant's id verbatim in the model field; nothing else in your code changes.
Frequently asked
- How do I call Claude Haiku 4.5 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-haiku-4.5". Nothing else in your code changes.
- What does Claude Haiku 4.5 cost in toman?
- 290,125 toman per 1M input tokens and 1,450,625 toman per 1M output tokens; a 1,000-word request is around 2,263 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Claude Haiku 4.5 take?
- Up to 200,000 tokens per request, roughly 150k words. A single answer can reach 64,000 tokens.
- Does Claude Haiku 4.5 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.