12B
Parameters
Dense Transformer
AIVory Smart Inference · Mistral
Open WeightMistral Nemo 12B - 128K context at 12B cost.
A 12B model with a 128K context window. That's unusual. Most models this size have 8K-32K context. Nemo gives you long-document capability at tiny-model pricing.
At a glance
Mistral Nemo 12B via Smart Inference.
Routed to the cheapest live provider on every request. Same model, lower bill.
128K
Context window
tokens per request
—
Cheapest input price
per 1M tokens via Smart Inference
—%
Cheaper
vs the priciest endpoint for the same model
Pricing
Mistral Nemo 12B: price comparison.
Our cheapest routed price vs what you'd pay elsewhere.
Prices in USD per 1M input tokens · updated live from the router
Quick start
Use Mistral Nemo 12B in three lines.
OpenAI-compatible. Swap your base_url, keep everything else.
from openai import OpenAI
client = OpenAI(
base_url="https://smart.aivory.net/v1",
api_key="sk-aivory-...",
)
resp = client.chat.completions.create(
model="mistral-nemo-instruct-24-07",
messages=[{"role": "user", "content": "Ship it."}],
)
print(resp.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://smart.aivory.net/v1",
apiKey: process.env.AIVORY_API_KEY,
});
const resp = await client.chat.completions.create({
model: "mistral-nemo-instruct-24-07",
messages: [{ role: "user", content: "Ship it." }],
});
console.log(resp.choices[0].message.content);curl https://smart.aivory.net/v1/chat/completions \
-H "Authorization: Bearer $AIVORY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "mistral-nemo-instruct-24-07",
"messages": [{"role": "user", "content": "Ship it."}]
}'That's the whole migration. Get early access and try it →
Use cases
What Mistral Nemo 12B is great at.
-
Long-Document Processing on a Budget
Feed a 50K-token document to a 12B model. Most small models can't do this (8K context). Nemo can. Summarize legal contracts, extract terms from policy documents, or parse long API responses without chunking.
-
High-Volume Classification
Process millions of text snippets: sentiment, topic, intent, language detection. At 12B parameters, each classification costs next to nothing. Run it against your entire backlog without worrying about spend.
-
Lightweight RAG Pipelines
Use Nemo as the answer-generation step in a retrieval pipeline. It's fast enough for real-time responses and cheap enough to serve every query. The 128K context fits large retrieval windows.
FAQ
Common questions.
What does Mistral Nemo 12B cost on AIVory?
One of the cheapest models available. The 12B parameter count means providers serve it on smaller GPUs with faster throughput. Check the live table above for exact rates.
When should I use Nemo vs a 70B model?
Use Nemo for tasks where speed and cost matter more than accuracy: classification, extraction, simple summaries, and RAG answer generation. Move to a 70B model when output quality drops below your bar.
Why does a 12B model have 128K context?
Mistral used RoPE scaling and efficient attention during training. Context window size is independent of parameter count. Nemo proves you can have both a small model and a large context.
How does Nemo compare to Gemma 2 9B?
Nemo has 128K context vs Gemma 2's 8K. That's a 16x difference. Nemo is also slightly larger (12B vs 9B). For anything involving long inputs, Nemo wins. For ultra-minimal edge deployment, Gemma 2 is smaller.
Start using Mistral Nemo 12B. Today.
Swap your base_url, keep shipping.
The router is live. Credits from $10, no subscription, no commitment.