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Gemini 2.5 Flash Lite API: toman pricing and code

google/gemini-2.5-flash-lite

Image inputTool callingReasoningJSON outputFile inputAudio input
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Input · per 1M tokens
34,622 toman
Output · per 1M tokens
138,488 toman
One 1,000-word request ≈
225 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 3,462 toman per 1M tokens. Reasoning tokens: 138,488 toman per 1M tokens. Per input image: 0.03 toman. Web search: 4,847.07 toman per request.Pricing and top-ups

Gemini 2.5 Flash Lite 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": "google/gemini-2.5-flash-lite",
    "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="google/gemini-2.5-flash-lite",
    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: "google/gemini-2.5-flash-lite",
  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 Gemini 2.5 Flash Lite good for?

Gemini 2.5 Flash Lite comes from Google; in uttapen you reach it with the model id "google/gemini-2.5-flash-lite". It accepts up to 1,048,576 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 65,535 tokens. On price it sits in the "very cheap" band — cheaper than 317 and dearer than 74 of the other paid models in the catalogue.

What it can do beyond plain text: it reads images directly, which makes it a real option for invoices, forms and screenshots; it takes files such as PDFs as input; it accepts audio 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.

Pricing is 34,622 toman per 1M input tokens and 138,488 per 1M output tokens. A 1,000-word round trip on Gemini 2.5 Flash Lite lands near 225 toman. It supports cached input: repeated context is billed at 3,462 toman per 1M, which matters a lot if your system prompt is long. Each input image is billed separately at about 0.03 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 Seed-2.0-Mini, and Gemini 2.5 Flash Lite costs about the same, 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 444 thousand-word requests on Gemini 2.5 Flash Lite, and every 1,000 toman is about 4,444 words of round trip. A job with one million input tokens and one million output tokens comes to 173,110 toman in total. Filling this model's 1,048,576-token window costs 36,304 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "google/gemini-3.1-flash-lite:batch", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out about 44% cheaper (225 against 394 toman). Maximum answer length differs as well: 65,535 against 65,536 tokens. On parameters the other takes reasoning_effort.

Google has 43 models in our catalogue; the cheapest is Gemma 4 26B A4B at 67 toman per thousand words and the dearest Gemini 3.1 Pro Preview Custom Tools at 6,301. By context size the nearest option from another provider is DeepSeek V4 Flash 0423 at 1,048,576 tokens.

Good fits: 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.

Provider's own description

Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...

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 out107 toman
Summarising a ten-page document4,000 in + 600 out222 toman
Classifying a thousand short rows120,000 in + 20,000 out6,924 toman

Frequently asked

How do I call Gemini 2.5 Flash Lite 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 "google/gemini-2.5-flash-lite". Nothing else in your code changes.
What does Gemini 2.5 Flash Lite cost in toman?
34,622 toman per 1M input tokens and 138,488 toman per 1M output tokens; a 1,000-word request is around 225 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Gemini 2.5 Flash Lite take?
Up to 1,048,576 tokens per request, roughly 786k words. A single answer can reach 65,535 tokens.
Does Gemini 2.5 Flash Lite 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.