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DeepSeek V3.1 API: toman pricing and code

deepseek/deepseek-chat-v3.1

Tool callingReasoningJSON output
Create a keyTry it
Input · per 1M tokens
86,555 toman
Output · per 1M tokens
328,908 toman
One 1,000-word request ≈
540 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 45,009 toman per 1M tokens.Pricing and top-ups

DeepSeek V3.1 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="deepseek/deepseek-chat-v3.1",
    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: "deepseek/deepseek-chat-v3.1",
  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": "deepseek/deepseek-chat-v3.1",
    "messages": [{"role": "user", "content": "Classify the ticket and give it a priority from 1 to 5."}],
    "response_format": {"type": "json_object"}
  }'

What is DeepSeek V3.1 good for?

DeepSeek V3.1 comes from DeepSeek; in uttapen you reach it with the model id "deepseek/deepseek-chat-v3.1". It accepts up to 163,840 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 147,456 tokens. On price it sits in the "cheap" band — cheaper than 259 and dearer than 138 of the other paid models in the catalogue.

What it can do beyond plain text: 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 86,555 toman per 1M input tokens and 328,908 per 1M output tokens. A 1,000-word round trip on DeepSeek V3.1 lands near 540 toman. It supports cached input: repeated context is billed at 45,009 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 MiniMax M2.5, and DeepSeek V3.1 costs about the same, 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 185 thousand-word requests on DeepSeek V3.1, and every 1,000 toman is about 1,852 words of round trip. A job with one million input tokens and one million output tokens comes to 415,463 toman in total. Filling this model's 163,840-token window costs 14,181 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "deepseek/deepseek-v3.1-terminus", and choosing between those two is where most people hesitate. Both land at nearly the same price on a thousand-word request (540 and 572 toman). On parameters, this one takes logit_bias, logprobs, min_p, presence_penalty.

DeepSeek has 18 models in our catalogue; the cheapest is DeepSeek V4 Flash 0423 at 123 toman per thousand words and the dearest DeepSeek Pro Latest at 3,642. Among the less common parameters it accepts logit_bias, logprobs, min_p, presence_penalty, repetition_penalty, top_k — all through the standard request body. By context size the nearest option from another provider is Llama Guard 4 12B at 163,840 tokens.

Good fits: high-volume work such as classification, tagging and bulk summarising, logic puzzles and code review, agents that reach out to APIs and databases, extracting data against a fixed schema.

Provider's own description

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

Three real jobs, priced on this model

Each figure is derived from the prices above and moves when they do.

JobTokensCost
One chat turn with a medium history1,500 in + 400 out261 toman
Summarising a ten-page document4,000 in + 600 out544 toman
Classifying a thousand short rows120,000 in + 20,000 out16,965 toman

Price history

DateInput (toman/1M)Output (toman/1M)
8 Sep 202686,555328,908
7 Sep 2026190,421571,262

Every price change for this model is recorded. Toman figures use today's rate.

Frequently asked

How do I call DeepSeek V3.1 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 "deepseek/deepseek-chat-v3.1". Nothing else in your code changes.
What does DeepSeek V3.1 cost in toman?
86,555 toman per 1M input tokens and 328,908 toman per 1M output tokens; a 1,000-word request is around 540 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does DeepSeek V3.1 take?
Up to 163,840 tokens per request, roughly 123k words. A single answer can reach 147,456 tokens.
Does DeepSeek V3.1 support streaming and tool calling?
Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Structured output through response_format works too.