---
title: Llama 3.1 Nemotron 70B Instruct — Top LLM | ModelsLab
description: Access Llama 3.1 Nemotron 70B Instruct HF via API for helpful responses topping Arena Hard 85.0. Try this NVIDIA-tuned 70B model now.
url: https://modelslab.com/llama-31-nemotron-70b-instruct-hf
canonical: https://modelslab.com/llama-31-nemotron-70b-instruct-hf
type: website
component: Seo/ModelPage
generated_at: 2026-04-15T02:07:53.728850Z
---

Available now on ModelsLab · Language Model

Llama 3.1 Nemotron 70B Instruct HF
Helpful Responses Top Benchmarks
---

[Try Llama 3.1 Nemotron 70B Instruct HF](/models/meta/nvidia-Llama-3.1-Nemotron-70B-Instruct-HF) [API Documentation](https://docs.modelslab.com)

Deploy Nemotron 70B Now
---

Arena Leader

### 85.0 Arena Hard

Leads automatic alignment benchmarks over GPT-4o and Claude 3.5 Sonnet.

128K Context

### Process Long Inputs

Handles 128k token context window for extended conversations and documents.

RLHF Tuned

### NVIDIA Helpfulness Boost

Fine-tuned with REINFORCE on Llama-3.1-70B-Instruct for precise user responses.

Examples

See what Llama 3.1 Nemotron 70B Instruct HF can create
---

Copy any prompt below and try it yourself in the [playground](/models/meta/nvidia-Llama-3.1-Nemotron-70B-Instruct-HF).

Code Review

“Review this Python function for efficiency and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)”

Tech Summary

“Summarize key advancements in transformer models since 2017, focusing on efficiency improvements and scaling laws.”

Data Analysis

“Analyze this dataset of sales figures by quarter and predict Q5 trend: Q1: 1200, Q2: 1500, Q3: 1800, Q4: 2100.”

Architecture Design

“Design a scalable microservices architecture for a cloud-based e-commerce platform handling 10k requests per second.”

For Developers

A few lines of code.
Nemotron 70B. One API call.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Llama 3.1 Nemotron 70B Instruct HF
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[Read the docs ](https://docs.modelslab.com)

### What is Llama 3.1 Nemotron 70B Instruct HF?

### How to use Llama 3.1 Nemotron 70B Instruct HF API?

### What are Llama 3.1 Nemotron 70B Instruct HF benchmarks?

### Is Llama 3.1 Nemotron 70B Instruct HF model fast?

### Llama 3.1 Nemotron 70B Instruct HF alternative options?

### What context length for llama 3.1 nemotron 70b instruct hf?

Ready to create?
---

Start generating with Llama 3.1 Nemotron 70B Instruct HF on ModelsLab.

[Try Llama 3.1 Nemotron 70B Instruct HF](/models/meta/nvidia-Llama-3.1-Nemotron-70B-Instruct-HF) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

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*Generated by ModelsLab - 2026-04-15*