DeepSeek V4 Flash Vision Exp API: toman pricing and code
deepseek/deepseek-v4-flash-vision-exp
visiontoolsreasoningjsonYou are billed for the usage the request actually reported. Prices follow the market. Cached input: 2,031 toman / 1M.Pricing and top-ups
DeepSeek V4 Flash Vision Exp 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": "deepseek/deepseek-v4-flash-vision-exp",
"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="deepseek/deepseek-v4-flash-vision-exp",
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: "deepseek/deepseek-v4-flash-vision-exp",
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 DeepSeek V4 Flash Vision Exp good for?
DeepSeek V4 Flash Vision Exp is one of DeepSeek's models. Put "deepseek/deepseek-v4-flash-vision-exp" in the model field and the rest of your code stays as it is. DeepSeek V4 Flash Vision Exp keeps 1,048,576 tokens in view at once, and that number is what caps the conversation history in your product. A single response can run to 384,000 tokens. On price it sits in the "cheap" band — cheaper than 110 and dearer than 296 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; 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.
For a back-of-envelope figure: about 332 toman per 1,000-word exchange (63,828 in, 191,483 out, per 1M tokens). It supports cached input: repeated context is billed at 2,031 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-5.4 Nano (batch): DeepSeek V4 Flash Vision Exp works out roughly 1.2× more expensive, and its context window is larger. 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 301 thousand-word requests on DeepSeek V4 Flash Vision Exp, and every 1,000 toman is about 3,012 words of round trip. A job with one million input tokens and one million output tokens comes to 255,310 toman in total. Filling this model's 1,048,576-token window costs 66,928 toman on the input side alone, which is the real reason to keep conversation history short.
DeepSeek has 17 models in our catalogue; the cheapest is DeepSeek V4 Flash Latest at 79 toman per thousand words and the dearest DeepSeek V4 Pro 0813 (batch) at 1,991. Among the less common parameters it accepts logit_bias, logprobs, min_p, reasoning_effort, repetition_penalty, top_k — all through the standard request body. By context size the nearest option from another provider is Gemini 2.5 Flash at 1,048,576 tokens.
What to use it for: high-volume work such as classification, tagging and bulk summarising, 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.
DeepSeek V4 Flash Vision Exp is an experimental vision-enabled version of [DeepSeek V4 Flash 0731](https://openrouter.ai/deepseek/deepseek-v4-flash-0731) from DeepSeek, adding image understanding while matching the base model on text capabilities including agents,...
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 | 172 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 370 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 11,489 toman |
Price history
| Date | Input (toman/1M) | Output (toman/1M) |
|---|---|---|
| 2026-09-07 | 63,828 | 191,483 |
| 2026-09-07 | 127,655 | 382,965 |
| 2026-09-07 | 63,828 | 191,483 |
| 2026-09-07 | 127,655 | 382,965 |
| 2026-09-06 | 63,828 | 191,483 |
Every price change for this model is recorded. Toman figures use today's rate.
Frequently asked
- How do I call DeepSeek V4 Flash Vision Exp 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-v4-flash-vision-exp". Nothing else in your code changes.
- What does DeepSeek V4 Flash Vision Exp cost in toman?
- 63,828 toman per 1M input tokens and 191,483 toman per 1M output tokens; a 1,000-word request is around 332 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does DeepSeek V4 Flash Vision Exp take?
- Up to 1,048,576 tokens per request, roughly 786k words. A single answer can reach 384,000 tokens.
- Does DeepSeek V4 Flash Vision Exp 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.