What are the hardware requirements for Meta Llama Llama 4 Scout 17B 16E Fp16?

Meta Llama Llama 4 Scout 17B 16E Fp16 requires approximately 207.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Meta Llama Llama 4 Scout 17B 16E Fp16 and how large is it?

Meta Llama Llama 4 Scout 17B 16E Fp16 is developed by mlx-community, a model with 17b 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 Meta Llama Llama 4 Scout 17B 16E Fp16?

Meta Llama Llama 4 Scout 17B 16E Fp16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Meta Llama Llama 4 Scout 17B 16E Fp16 by mlx-community — VRAM 207.3GB

Name: Meta Llama Llama 4 Scout 17B 16E Fp16
Author: mlx-community

Meta Llama Llama 4 Scout 17B 16E Fp16 is an open-source language model by mlx-community. Features: 17b LLM, VRAM: 207.3GB, License: other, Quantized, LLM Explorer Score: 0.18.

Ar Base model:finetune:meta-llama... Base model:meta-llama/llama-4-... Conversational De En Es Facebook Fp16 Fr Hi Id It Llama Llama-4 Llama4 Meta Mlx Pt Pytorch Quantized Region:us Safetensors Sharded Tensorflow Th Tl Vi

Model Card on HF 🤗: https://huggingface.co/mlx-community/meta-llama-Llama-4-Scout-17B-16E-fp16

Meta Llama Llama 4 Scout 17B 16E Fp16 Parameters and Internals

LLM Name	Meta Llama Llama 4 Scout 17B 16E Fp16
Repository 🤗	https://huggingface.co/mlx-community/meta-llama-Llama-4-Scout-17B-16E-fp16
Base Model(s)	meta-llama/Llama-4-Scout-17B-16E meta-llama/Llama-4-Scout-17B-16E
Model Size	17b
Required VRAM	207.3 GB
Updated	2026-07-19
Maintainer	mlx-community
Model Type	llama4
Model Files	4.9 GB: 1-of-49 4.4 GB: 2-of-49 4.4 GB: 3-of-49 4.4 GB: 4-of-49 4.4 GB: 5-of-49 4.4 GB: 6-of-49 4.4 GB: 7-of-49 4.4 GB: 8-of-49 4.4 GB: 9-of-49 4.4 GB: 10-of-49 4.4 GB: 11-of-49 4.4 GB: 12-of-49 4.4 GB: 13-of-49 4.4 GB: 14-of-49 4.4 GB: 15-of-49 4.4 GB: 16-of-49 4.4 GB: 17-of-49 4.4 GB: 18-of-49 4.4 GB: 19-of-49 4.4 GB: 20-of-49 4.4 GB: 21-of-49 4.4 GB: 22-of-49 4.4 GB: 23-of-49 4.4 GB: 24-of-49 4.4 GB: 25-of-49 4.4 GB: 26-of-49 4.4 GB: 27-of-49 4.4 GB: 28-of-49 4.4 GB: 29-of-49 4.4 GB: 30-of-49 4.4 GB: 31-of-49 4.4 GB: 32-of-49 4.4 GB: 33-of-49 4.4 GB: 34-of-49 4.4 GB: 35-of-49 4.4 GB: 36-of-49 4.4 GB: 37-of-49 4.4 GB: 38-of-49 4.4 GB: 39-of-49 4.4 GB: 40-of-49 4.4 GB: 41-of-49 4.4 GB: 42-of-49 4.4 GB: 43-of-49 4.4 GB: 44-of-49 4.4 GB: 45-of-49 4.4 GB: 46-of-49 4.4 GB: 47-of-49
Supported Languages	ar de en es fr hi id it pt th tl vi
Quantization Type	fp16
Model Architecture	Llama4ForConditionalGeneration
License	other
Transformers Version	4.51.0.dev0

Rank the Meta Llama Llama 4 Scout 17B 16E Fp16 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 Meta Llama Llama 4 Scout 17B 16E Fp16

Best Alternatives	Context / RAM	Downloads	Likes
...Maverick 17B 16E Instruct 4bit	0K / 146.3 GB	419	7
... 4 Scout 17B 16E Instruct 6bit	0K / 88.8 GB	333	5
...averick 17B 128E Instruct 6bit	0K / 201.1 GB	125	1
... 4 Scout 17B 16E Instruct 4bit	0K / 61 GB	1203	12
... 4 Scout 17B 16E Instruct 8bit	0K / 114.7 GB	588	4
...Scout 17B 16E Unsloth Bnb 4bit	0K / 60.6 GB	562	5
... 16E Instruct Unsloth Bnb 4bit	0K / 60.6 GB	205	80
...ama Llama 4 Scout 17B 16E 4bit	0K / 60.5 GB	338	8
...averick 17B 128E Instruct 4bit	0K / 140.8 GB	204	2
Llama 4 Scout 17B 16E 4bit	0K / 61 GB	163	2

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/meta-llama-Llama-4-Scout-17B-16E-fp16.