Models / MetaLlama / / Llama 3.1 Nemotron 70B Instruct API
Llama 3.1 Nemotron 70B Instruct API
LLM
Custom NVIDIA LLM optimized to enhance the helpfulness and relevance of generated responses to user queries.
Try our Llama 3.1 API

API Usage
How to use Llama 3.1 Nemotron 70B InstructModel CardPrompting Llama 3.1 Nemotron 70B InstructApplications & Use CasesLlama 3.1 Nemotron 70B Instruct API Usage
Endpoint
nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
curl -X POST "https://api.together.xyz/v1/chat/completions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"messages": [
{
"role": "user",
"content": "What are some fun things to do in New York?"
}
]
}'
curl -X POST "https://api.together.xyz/v1/images/generations" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"prompt": "Draw an anime style version of this image.",
"width": 1024,
"height": 768,
"steps": 28,
"n": 1,
"response_format": "url",
"image_url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"
}'
curl -X POST https://api.together.xyz/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d '{
"model": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"messages": [{
"role": "user",
"content": [
{"type": "text", "text": "Describe what you see in this image."},
{"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
]
}],
"max_tokens": 512
}'
curl -X POST https://api.together.xyz/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d '{
"model": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"messages": [{
"role": "user",
"content": "Given two binary strings `a` and `b`, return their sum as a binary string"
}]
}'
curl -X POST https://api.together.xyz/v1/rerank \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d '{
"model": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"query": "What animals can I find near Peru?",
"documents": [
"The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
"The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
"The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
"The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
],
"top_n": 2
}'
curl -X POST https://api.together.xyz/v1/embeddings \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": "Our solar system orbits the Milky Way galaxy at about 515,000 mph.",
"model": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"
}'
curl -X POST https://api.together.xyz/v1/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-d '{
"model": "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
"prompt": "A horse is a horse",
"max_tokens": 32,
"temperature": 0.1,
"safety_model": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"
}'
curl --location 'https://api.together.ai/v1/audio/generations' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer $TOGETHER_API_KEY' \
--output speech.mp3 \
--data '{
"input": "Today is a wonderful day to build something people love!",
"voice": "helpful woman",
"response_format": "mp3",
"sample_rate": 44100,
"stream": false,
"model": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"
}'
curl -X POST "https://api.together.xyz/v1/audio/transcriptions" \
-H "Authorization: Bearer $TOGETHER_API_KEY" \
-F "model=nvidia/Llama-3.1-Nemotron-70B-Instruct-HF" \
-F "language=en" \
-F "response_format=json" \
-F "timestamp_granularities=segment"
from together import Together
client = Together()
response = client.chat.completions.create(
model="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
messages=[
{
"role": "user",
"content": "What are some fun things to do in New York?"
}
]
)
print(response.choices[0].message.content)
from together import Together
client = Together()
imageCompletion = client.images.generate(
model="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
width=1024,
height=768,
steps=28,
prompt="Draw an anime style version of this image.",
image_url="https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
)
print(imageCompletion.data[0].url)
from together import Together
client = Together()
response = client.chat.completions.create(
model="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
messages=[{
"role": "user",
"content": [
{"type": "text", "text": "Describe what you see in this image."},
{"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
]
}]
)
print(response.choices[0].message.content)
from together import Together
client = Together()
response = client.chat.completions.create(
model="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
messages=[
{
"role": "user",
"content": "Given two binary strings `a` and `b`, return their sum as a binary string"
}
],
)
print(response.choices[0].message.content)
from together import Together
client = Together()
query = "What animals can I find near Peru?"
documents = [
"The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
"The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
"The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
"The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations.",
]
response = client.rerank.create(
model="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
query=query,
documents=documents,
top_n=2
)
for result in response.results:
print(f"Relevance Score: {result.relevance_score}")
from together import Together
client = Together()
response = client.embeddings.create(
model = "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
input = "Our solar system orbits the Milky Way galaxy at about 515,000 mph"
)
from together import Together
client = Together()
response = client.completions.create(
model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
prompt="A horse is a horse",
max_tokens=32,
temperature=0.1,
safety_model="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
)
print(response.choices[0].text)
from together import Together
client = Together()
speech_file_path = "speech.mp3"
response = client.audio.speech.create(
model="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
input="Today is a wonderful day to build something people love!",
voice="helpful woman",
)
response.stream_to_file(speech_file_path)
from together import Together
client = Together()
response = client.audio.transcribe(
model="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
language="en",
response_format="json",
timestamp_granularities="segment"
)
print(response.text)
import Together from 'together-ai';
const together = new Together();
const completion = await together.chat.completions.create({
model: 'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF',
messages: [
{
role: 'user',
content: 'What are some fun things to do in New York?'
}
],
});
console.log(completion.choices[0].message.content);
import Together from "together-ai";
const together = new Together();
async function main() {
const response = await together.images.create({
model: "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
width: 1024,
height: 1024,
steps: 28,
prompt: "Draw an anime style version of this image.",
image_url: "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
});
console.log(response.data[0].url);
}
main();
import Together from "together-ai";
const together = new Together();
const imageUrl = "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png";
async function main() {
const response = await together.chat.completions.create({
model: "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
messages: [{
role: "user",
content: [
{ type: "text", text: "Describe what you see in this image." },
{ type: "image_url", image_url: { url: imageUrl } }
]
}]
});
console.log(response.choices[0]?.message?.content);
}
main();
import Together from "together-ai";
const together = new Together();
async function main() {
const response = await together.chat.completions.create({
model: "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
messages: [{
role: "user",
content: "Given two binary strings `a` and `b`, return their sum as a binary string"
}]
});
console.log(response.choices[0]?.message?.content);
}
main();
import Together from "together-ai";
const together = new Together();
const query = "What animals can I find near Peru?";
const documents = [
"The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
"The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
"The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
"The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
];
async function main() {
const response = await together.rerank.create({
model: "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
query: query,
documents: documents,
top_n: 2
});
for (const result of response.results) {
console.log(`Relevance Score: ${result.relevance_score}`);
}
}
main();
import Together from "together-ai";
const together = new Together();
const response = await client.embeddings.create({
model: 'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF',
input: 'Our solar system orbits the Milky Way galaxy at about 515,000 mph',
});
import Together from "together-ai";
const together = new Together();
async function main() {
const response = await together.completions.create({
model: "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
prompt: "A horse is a horse",
max_tokens: 32,
temperature: 0.1,
safety_model: "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"
});
console.log(response.choices[0]?.text);
}
main();
import Together from 'together-ai';
const together = new Together();
async function generateAudio() {
const res = await together.audio.create({
input: 'Today is a wonderful day to build something people love!',
voice: 'helpful woman',
response_format: 'mp3',
sample_rate: 44100,
stream: false,
model: 'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF',
});
if (res.body) {
console.log(res.body);
const nodeStream = Readable.from(res.body as ReadableStream);
const fileStream = createWriteStream('./speech.mp3');
nodeStream.pipe(fileStream);
}
}
generateAudio();
import Together from "together-ai";
const together = new Together();
const response = await together.audio.transcriptions.create(
model: "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
language: "en",
response_format: "json",
timestamp_granularities: "segment"
});
console.log(response)
How to use Llama 3.1 Nemotron 70B Instruct
Model details
Prompting Llama 3.1 Nemotron 70B Instruct
Applications & Use Cases
Model Provider:
Meta
Type:
Chat
Variant:
Nemotron
Parameters:
70B
Deployment:
✔ Serverless
✔ On-Demand Dedicated
✔ Monthly Reserved
Quantization
FP16
Context length:
128K
Pricing:
$0.88
Check pricing
Run in playground
Deploy model
Quickstart docs
Quickstart docs
Serverless
Monthly Reserved
Looking for production scale? Deploy on a dedicated endpoint
Deploy Llama 3.1 Nemotron 70B Instruct on a dedicated endpoint with custom hardware configuration, as many instances as you need, and auto-scaling.
