What are the hardware requirements for Llama 3.1 70B Instruct FP8?

Llama 3.1 70B Instruct FP8 requires approximately 72.7 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 3.1 70B Instruct FP8 and how large is it?

Llama 3.1 70B Instruct FP8 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 3.1 70B Instruct FP8?

Llama 3.1 70B Instruct FP8 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3.1 70B Instruct FP8 by nvidia — VRAM 72.7GB, 128K context

Name: Llama 3.1 70B Instruct FP8
Author: nvidia

Llama 3.1 70B Instruct FP8 is an open-source language model by nvidia. Features: 70b LLM, VRAM: 72.7GB, Context: 128K, License: llama3.1, Instruction-Based, LLM Explorer Score: 0.17.

Base model:finetune:meta-llama... Base model:meta-llama/llama-3.... Conversational Endpoints compatible Instruct Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/nvidia/Llama-3.1-70B-Instruct-FP8

Llama 3.1 70B Instruct FP8 Parameters and Internals

LLM Name	Llama 3.1 70B Instruct FP8
Repository 🤗	https://huggingface.co/nvidia/Llama-3.1-70B-Instruct-FP8
Base Model(s)	meta-llama/Llama-3.1-70B-Instruct meta-llama/Llama-3.1-70B-Instruct
Model Size	70b
Required VRAM	72.7 GB
Updated	2026-07-22
Maintainer	nvidia
Model Type	llama
Instruction-Based	Yes
Model Files	4.8 GB: 1-of-15 5.0 GB: 2-of-15 4.9 GB: 3-of-15 4.9 GB: 4-of-15 4.9 GB: 5-of-15 5.0 GB: 6-of-15 4.9 GB: 7-of-15 4.9 GB: 8-of-15 4.9 GB: 9-of-15 5.0 GB: 10-of-15 4.9 GB: 11-of-15 4.9 GB: 12-of-15 4.9 GB: 13-of-15 5.0 GB: 14-of-15 3.8 GB: 15-of-15
Model Architecture	LlamaForCausalLM
License	llama3.1
Context Length	131072
Model Max Length	131072
Transformers Version	4.44.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama 3.1 70B Instruct FP8 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 3.1 70B Instruct FP8

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-3.1-70B-Instruct-FP8.