NVIDIA: Llama 3.1 Nemotron 70B Instruct
nvidia/llama-3.1-nemotron-70b-instruct
Access Llama 3.1 Nemotron 70B Instruct from NVIDIA using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "nvidia/llama-3.1-nemotron-70b-instruct"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "nvidia/llama-3.1-nemotron-70b-instruct"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="nvidia/llama-3.1-nemotron-70b-instruct",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "nvidia/llama-3.1-nemotron-70b-instruct",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Llama 3.1 Nemotron 70B Instruct is a 70B parameter LLM customized by NVIDIA using RLHF to improve response helpfulness, achieving top rankings on alignment benchmarks like Arena Hard and AlpacaEval 2 LC. It supports a 128K token context and is optimized for conversational AI and instruction-following tasks.
Context Window 131K
tokens
Max Output 16K
tokens
Input Cost $1.2
per million tokens
Output Cost $1.2
per million tokens
Release Date Oct 1, 2024
Output Speed 47
tokens / sec
Latency 0.34s
time to first token
Model Playground
Try Llama 3.1 Nemotron 70B Instruct instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Llama 3.1 Nemotron 70B Instruct performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 46.5% |
| Humanity's Last Exam Cross-domain reasoning | 4.6% |
| LiveCodeBench Recent coding problems | 16.9% |
| SciCode Scientific programming | 23.3% |
| MATH-500 Competition math | 73.3% |
| AIME 2024 Advanced math exam | 24.7% |
| AIME 2025 Advanced math exam | 11.0% |
| IFBench Instruction following | 30.7% |
| LCR Long-context reasoning | 7.0% |
| Terminal-Bench Hard Agentic terminal tasks | 4.5% |
| τ²-Bench Tool use / agents | 23.1% |
Scores sourced from Artificial Analysis.
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Frequently Asked Questions
You can access Llama 3.1 Nemotron 70B Instruct by NVIDIA through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Llama 3.1 Nemotron 70B Instruct to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $1.2 |
| Output | $1.2 |
Llama 3.1 Nemotron 70B Instruct was created by NVIDIA and released on Oct 1, 2024.
Llama 3.1 Nemotron 70B Instruct supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Llama 3.1 Nemotron 70B Instruct can generate up to 16K tokens in a single response.
Yes — the Llama 3.1 Nemotron 70B Instruct API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add Llama 3.1 Nemotron 70B Instruct to your app without worrying about API keys or setup.
Read the Docs View Tutorials