What are the hardware requirements for FastVLM 7B?

FastVLM 7B requires approximately 15.5 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed FastVLM 7B and how large is it?

FastVLM 7B is developed by apple, a model with 7b 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 FastVLM 7B?

FastVLM 7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

FastVLM 7B by apple — VRAM 15.5GB, 32K context

Name: FastVLM 7B
Author: apple

FastVLM 7B is an open-source language model by apple. Features: 7b LLM, VRAM: 15.5GB, Context: 32K, License: apple-amlr, LLM Explorer Score: 0.24.

Arxiv:2412.13303 Conversational Custom code Llava qwen2 Ml-fastvlm Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/apple/FastVLM-7B

FastVLM 7B Parameters and Internals

LLM Name	FastVLM 7B
Repository 🤗	https://huggingface.co/apple/FastVLM-7B
Model Size	7b
Required VRAM	15.5 GB
Updated	2026-08-03
Maintainer	apple
Model Type	llava_qwen2
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.6 GB: 3-of-4 1.1 GB: 4-of-4 0.0 GB
Model Architecture	LlavaQwen2ForCausalLM
License	apple-amlr
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the FastVLM 7B capabilities

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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 FastVLM 7B

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HuatuoGPT Vision 7B	128K / 15.9 GB	1632	30
Bumblebee Light	32K / 18.6 GB	5	1