NVIDIA: Llama 3.1 Nemotron 70B Instruct
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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
Code Example
Add AI to your app with the Puter.js AI API, no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").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").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
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ChatNemotron 3.5 Lightning
Nemotron 3.5 Lightning is a 30B-parameter Mixture-of-Experts model from NVIDIA with 3B active parameters per token, using a hybrid Mamba-2, MoE, and attention layer architecture. It is designed for high-volume, low-latency execution inside multi-agent systems, where a larger reasoning model like Nemotron 3 Ultra plans and delegates, and Lightning handles tool calls, code review, and other repetitive subagent tasks. NVIDIA reports up to 4x higher output throughput than similarly sized open models and, on its PinchBench agent benchmark, 86% accuracy while completing 10,000 tasks 30% faster than Qwen3.6 35B at similar accuracy. The model ships with built-in multi-token prediction and draft models for speculative decoding, and is available in NVFP4 and BF16 checkpoints under the permissive OpenMDW-1.1 license with open weights and training recipes. Choose it for agent harnesses handling frequent, narrow calls, tool validation, or subagent delegation where response speed matters more than broad reasoning depth.
ChatNemotron 3 Ultra 550B A55B
Nemotron 3 Ultra 550B A55B is NVIDIA's open-weight frontier reasoning model with 550B total and 55B active parameters, built on a hybrid Mamba-Transformer Mixture-of-Experts architecture. It supports a 1M token context window and is designed for long-running agentic workflows, complex multi-step reasoning, and high-accuracy tasks across code, math, and science. NVIDIA reports up to 5.9x higher inference throughput than comparable open MoE models. On the Artificial Analysis Intelligence Index it scores 48, leading US open-weight models and delivering the highest non-hallucination score in its comparison set (78.7 on AA-Omniscience). Choose it for production agentic pipelines, deep document analysis, or reasoning-heavy API workloads where both accuracy and throughput matter.
Frequently Asked Questions
Llama 3.1 Nemotron 70B Instruct is no longer available through Puter.js. Explore other AI models for alternatives.
| 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.
Llama 3.1 Nemotron 70B Instruct scores 6.9 on the Artificial Analysis Intelligence Index, outperforming 21% of tracked models. On math, it scores 11.0 (outperforms 14% of models).
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.
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