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Mistral: Mistral Nemo: AI model

Mistral Nemo is a 12B multilingual model built by Mistral with NVIDIA, offering a 128K-token context and broad language coverage at a low price. Reachable from inside Iran through Hormouz.

Context window:
131,072 tokens
Input:
$0.03/1M tokens
Output:
$0.03/1M tokens
Type:
text
  • Tools
  • Streaming
  • Long context

Mistral Nemo is a 12B-parameter model built by Mistral in collaboration with NVIDIA. It is multilingual by design, covering many major languages, and offers a 128K-token context window. A strong combination for a model of its modest size.

Its small footprint and low price make it a good general-purpose workhorse for chat, drafting and multilingual tasks where you want solid quality without flagship cost. It supports tool calling as well. It is served through Hormouz behind an OpenAI-compatible API: point your base URL at Hormouz, drop in a Hormouz key, and existing OpenAI SDK code runs unchanged.

Pricing is usage-based: $0.15 per million input tokens and $0.17 per million output tokens. Hormouz provides stable access from inside Iran, with no foreign credit card or circumvention tooling required.

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

Quickstart

curl https://api.hormouz.net/v1/chat/completions \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistralai/mistral-nemo",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Specs

VendorMistral AI
TypeText
Context window131,072 tokens
Pricing$0.03/M in · $0.03/M out
APIChat Completions
CapabilitiesStreaming · Tools

Code example

cURL
curl https://api.hormouz.net/v1/chat/completions \
  -H "Authorization: Bearer ng-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistralai/mistral-nemo",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
Python
from openai import OpenAI
client = OpenAI(api_key="ng-YOUR_API_KEY", base_url="https://api.hormouz.net/v1")
response = client.chat.completions.create(
    model="mistralai/mistral-nemo",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)
JavaScript
import OpenAI from "openai";
const client = new OpenAI({ apiKey: "ng-YOUR_API_KEY", baseURL: "https://api.hormouz.net/v1" });
const response = await client.chat.completions.create({
  model: "mistralai/mistral-nemo",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);

Buy the Mistral: Mistral Nemo API, paid in rial

  • Buy credit with an Iranian bank card; no foreign card or account needed.
  • One Hormouz key reaches Mistral: Mistral Nemo and 600+ other models, and you pay only for what you use.
  • No VPN and no risk of a banned account; just change the base URL to api.hormouz.net/v1.
Create an account

Use via Hormouz

Connect to this model and 600+ others with one API key, then see usage down to each request.

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FAQ

How much does Mistral Nemo cost?
Billing is usage-based: $0.15 per million input tokens and $0.17 per million output tokens. There is no fixed monthly fee. You pay only for what you use.
How do I access Mistral Nemo from inside Iran?
Create an account on Hormouz and generate an API key. Hormouz provides stable access from inside Iran, with no foreign credit card or circumvention tooling required.
Is Mistral Nemo compatible with OpenAI code?
Yes. Hormouz exposes an OpenAI-compatible API. Just change the base URL to Hormouz and swap in your Hormouz key. Your existing SDKs and code run without a rewrite.
Is Mistral Nemo good for multiple languages?
Yes. It was designed to be multilingual and covers many major languages, which makes it a practical low-cost choice for chat and drafting across languages.
When should I pick Mistral Nemo?
Pick it as an affordable general-purpose model for chat, drafting and multilingual tasks with a 128K-token context, when you do not need flagship-level reasoning.

Updated 2026-10-13