Lyria 3 Pro Preview API: toman pricing and code
google/lyria-3-pro-preview
visionjsonYou are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups
Lyria 3 Pro Preview 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/lyria-3-pro-preview",
"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/lyria-3-pro-preview",
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/lyria-3-pro-preview",
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 Lyria 3 Pro Preview good for?
Google publishes this model; we expose it under the id "google/lyria-3-pro-preview". Its context window is 1,048,576 tokens, roughly 786k English words in one request. A single response can run to 65,536 tokens. On price it sits in the "very cheap" band — cheaper than 0 and dearer than 406 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 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 0 toman per 1M input tokens and 0 per 1M output tokens. A 1,000-word round trip on Lyria 3 Pro Preview lands near 0 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 Nemotron 3.5 Content Safety (free), 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.
Its nearest relative in the catalogue is "google/lyria-3-clip-preview", and choosing between those two is where most people hesitate.
Google has 45 models in our catalogue; the cheapest is Gemma 3 4B at 57 toman per thousand words and the dearest Google Gemini Pro Latest at 5,280. 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 DeepSeek V4 Flash 0423 at 1,048,576 tokens.
Good fits: high-volume work such as classification, tagging and bulk summarising, pulling text and fields out of images, extracting data against a fixed schema, analysing a long document or codebase in one request.
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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 | 0 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 0 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 0 toman |
Frequently asked
- How do I call Lyria 3 Pro Preview 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/lyria-3-pro-preview". Nothing else in your code changes.
- What does Lyria 3 Pro Preview cost in toman?
- 0 toman per 1M input tokens and 0 toman per 1M output tokens; a 1,000-word request is around 0 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Lyria 3 Pro Preview take?
- Up to 1,048,576 tokens per request, roughly 786k words. A single answer can reach 65,536 tokens.
- Does Lyria 3 Pro Preview support streaming and image input?
- Streaming (stream=true) works on every model here. Image input is accepted through image_url, as a data URI or a public URL. Structured output through response_format works too.