Phi 4 API: toman pricing and code
microsoft/phi-4
You are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups
Phi 4 example: JSON output against a schema
The example is picked from this model's own capabilities. Drop in your key and it runs as is.
from openai import OpenAI
import json
client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")
schema = {
"name": "ticket",
"schema": {
"type": "object",
"properties": {
"category": {"type": "string", "enum": ["fani", "mali", "forush"]},
"priority": {"type": "integer", "minimum": 1, "maximum": 5},
"summary": {"type": "string"},
},
"required": ["category", "priority", "summary"],
"additionalProperties": False,
},
"strict": True,
}
resp = client.chat.completions.create(
model="microsoft/phi-4",
messages=[{"role": "user", "content": "Ticket: "For two days I cannot download my invoice and I was charged twice.""}],
response_format={"type": "json_schema", "json_schema": schema},
)
print(json.loads(resp.choices[0].message.content))import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });
const resp = await client.chat.completions.create({
model: "microsoft/phi-4",
messages: [{ role: "user", content: "Ticket: "For two days I cannot download my invoice and I was charged twice."" }],
response_format: {
type: "json_schema",
json_schema: {
name: "ticket",
strict: true,
schema: {
type: "object",
properties: {
category: { type: "string", enum: ["fani", "mali", "forush"] },
priority: { type: "integer", minimum: 1, maximum: 5 },
summary: { type: "string" },
},
required: ["category", "priority", "summary"],
additionalProperties: false,
},
},
},
});
console.log(JSON.parse(resp.choices[0].message.content));curl https://api.uttapen.ir/v1/chat/completions \
-H "Authorization: Bearer sk-up-…" \
-H "Content-Type: application/json" \
-d '{
"model": "microsoft/phi-4",
"messages": [{"role": "user", "content": "Classify the ticket and give it a priority from 1 to 5."}],
"response_format": {"type": "json_object"}
}'What is Phi 4 good for?
The id for Phi 4 in our API is "microsoft/
What it can do beyond plain text: it returns schema-valid JSON through response_format, ready to hand to your code. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper.
Pricing is 24,235 toman per 1M input tokens and 48,471 per 1M output tokens. A 1,000-word round trip on Phi 4 lands near 95 toman. 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 Command R7B (12-2024): Phi 4 works out about 10% 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 1,053 thousand-word requests on Phi 4, and every 1,000 toman is about 10,526 words of round trip. A job with one million input tokens and one million output tokens comes to 72,706 toman in total. Filling this model's 16,384-token window costs 397 toman on the input side alone, which is the real reason to keep conversation history short.
Among the less common parameters it accepts logit_bias, min_p, presence_penalty, repetition_penalty, top_k — all through the standard request body. It does not support include_reasoning, reasoning, tool_choice, tools, 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 Reka Edge at 16,384 tokens.
Good fits: high-volume work such as classification, tagging and bulk summarising, extracting data against a fixed schema.
[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...
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 | 56 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 126 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 3,878 toman |
Frequently asked
- How do I call Phi 4 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 "microsoft/ phi-4". Nothing else in your code changes. - What does Phi 4 cost in toman?
- 24,235 toman per 1M input tokens and 48,471 toman per 1M output tokens; a 1,000-word request is around 95 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Phi 4 take?
- Up to 16,384 tokens per request, roughly 12k words. A single answer can reach 14,745 tokens.
- Can I stream Phi 4's output?
- Yes — with stream=true you get SSE events as the tokens are produced. This model has no tool calling and no image input, so pick a different one if you need either.