What are the hardware requirements for Llama 3.3 Nemotron 70B Reward Principle?

Llama 3.3 Nemotron 70B Reward Principle requires approximately 141.9 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 3.3 Nemotron 70B Reward Principle and how large is it?

Llama 3.3 Nemotron 70B Reward Principle is developed by nvidia, a model with 70b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Llama 3.3 Nemotron 70B Reward Principle?

Llama 3.3 Nemotron 70B Reward Principle is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3.3 Nemotron 70B Reward Principle by nvidia — VRAM 141.9GB, 128K context

Name: Llama 3.3 Nemotron 70B Reward Principle
Author: nvidia

Llama 3.3 Nemotron 70B Reward Principle is an open-source language model by nvidia. Features: 70b LLM, VRAM: 141.9GB, Context: 128K, License: other, Instruction-Based, LLM Explorer Score: 0.21.

Arxiv:2310.05344 Arxiv:2311.09528 Arxiv:2406.08673 Arxiv:2410.01257 Arxiv:2410.16184 Arxiv:2503.04378 Arxiv:2505.11475 Arxiv:2509.21319 Base model:finetune:meta-llama... Base model:meta-llama/llama-3.... Conversational Dataset:nvidia/helpsteer3 En Instruct Llama Llama3.3 Nvidia Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/nvidia/Llama-3.3-Nemotron-70B-Reward-Principle

Llama 3.3 Nemotron 70B Reward Principle Parameters and Internals

LLM Name	Llama 3.3 Nemotron 70B Reward Principle
Repository 🤗	https://huggingface.co/nvidia/Llama-3.3-Nemotron-70B-Reward-Principle
Base Model(s)	meta-llama/Llama-3.3-70B-Instruct meta-llama/Llama-3.3-70B-Instruct
Model Size	70b
Required VRAM	141.9 GB
Updated	2026-07-12
Maintainer	nvidia
Model Type	llama
Instruction-Based	Yes
Model Files	4.6 GB: 1-of-30 4.7 GB: 2-of-30 5.0 GB: 3-of-30 5.0 GB: 4-of-30 4.7 GB: 5-of-30 4.7 GB: 6-of-30 4.7 GB: 7-of-30 5.0 GB: 8-of-30 5.0 GB: 9-of-30 4.7 GB: 10-of-30 4.7 GB: 11-of-30 4.7 GB: 12-of-30 5.0 GB: 13-of-30 5.0 GB: 14-of-30 4.7 GB: 15-of-30 4.7 GB: 16-of-30 4.7 GB: 17-of-30 5.0 GB: 18-of-30 5.0 GB: 19-of-30 4.7 GB: 20-of-30 4.7 GB: 21-of-30 4.7 GB: 22-of-30 5.0 GB: 23-of-30 5.0 GB: 24-of-30 4.7 GB: 25-of-30 4.7 GB: 26-of-30 4.7 GB: 27-of-30 5.0 GB: 28-of-30 5.0 GB: 29-of-30 2.1 GB: 30-of-30
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	other
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.0
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama 3.3 Nemotron 70B Reward Principle capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Llama 3.3 Nemotron 70B Reward Principle

Best Alternatives	Context / RAM	Downloads	Likes
... Chat 1048K Chinese Llama3 70B	1024K / 141.9 GB	9069	5
... Chat 1048K Chinese Llama3 70B	1024K / 141.9 GB	7684	4
... 3 70B Instruct Gradient 1048K	1024K / 141.9 GB	22	122
Llama3 Function Calling 1048K	1024K / 141.9 GB	5	1
...a 3 70B Instruct Gradient 524K	512K / 141.9 GB	24	23
...a 3 70B Instruct Gradient 262K	256K / 141.9 GB	20	56
...ama 3 70B Arimas Story RP V2.0	256K / 141.1 GB	10	3
...ama 3 70B Arimas Story RP V1.6	256K / 141.2 GB	5	0
...ama 3 70B Arimas Story RP V1.5	256K / 141.2 GB	21	3
Llama 3.1 70B Instruct	128K / 141.9 GB	813492	938

Note: green Score (e.g. "73.2") means that the model is better than nvidia/Llama-3.3-Nemotron-70B-Reward-Principle.