Nemotron 3 Nano Omni (free) API: toman pricing and code
nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free
Free · shared capacityvisiontoolsreasoningaudioYou are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups
Nemotron 3 Nano Omni (free) 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": "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free",
"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="nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free",
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: "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free",
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 Nemotron 3 Nano Omni (free) good for?
Nemotron 3 Nano Omni (free) comes from NVIDIA; in uttapen you reach it with the model id "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free". It accepts up to 256,000 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 65,536 tokens. Using it costs nothing. In exchange the capacity is shared, so during busy hours a request can come back empty-handed.
What it can do beyond plain text: it reads images directly, which makes it a real option for invoices, forms and screenshots; it accepts audio input; it supports tool calling, so it can invoke your own functions with valid arguments; 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 0 toman per 1M input tokens and 0 per 1M output tokens. A 1,000-word round trip on Nemotron 3 Nano Omni (free) 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 Dots3-Note Preview (free), 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.
NVIDIA has 10 models in our catalogue; the cheapest is Nemotron 3 Nano 30B A3B at 94 toman per thousand words and the dearest Nemotron 3 Ultra at 1,414. It does not support response_format, structured_outputs, 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 Command A at 256,000 tokens.
Good fits: proving an idea works before you spend anything, logic puzzles and code review, pulling text and fields out of images, agents that reach out to APIs and databases, analysing a long document or codebase in one request.
NVIDIA Nemotron™ 3 Nano Omni is a 30B-A3B open multimodal model designed to function as a perception and context sub-agent in enterprise agent systems. It accepts text, image, video, and...
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 Nemotron 3 Nano Omni (free) 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 "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free". Nothing else in your code changes.
- What does Nemotron 3 Nano Omni (free) 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 Nemotron 3 Nano Omni (free) take?
- Up to 256,000 tokens per request, roughly 192k words. A single answer can reach 65,536 tokens.
- Does Nemotron 3 Nano Omni (free) 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.
- What are the limits on a free model?
- Free models have a daily per-user cap and their capacity is shared with everyone else. When the shared pool is exhausted the request is refused with a clear error and your wallet is untouched.