FastVLM
This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025 - apple-aiml-research/ml-fastvlm
This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025 - apple-aiml-research/ml-fastvlm
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FastVLM is a practical fit for buyers evaluating AI model, Development and Tools, and #Visual Model tools.
- Who is it for?
- ML engineers building on-device vision-language features who need low-latency image description; better than LLaVA-OneVision for TTFT on Apple Silicon and iOS.
- Pricing
- freemium
Product information
What this product does
This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025 - apple-aiml-research/ml-fastvlm
Sourced from github.com
Works With
Platforms
- Web
- iOS
AI Models
- Qwen2-7B
- LLaVA-OneVision-0.5B
- Cambrian-1-8B
Problem Solved
What problem does FastVLM solve?
Company & Maker
Who built FastVLM?
- Company
- Apple
- Product
- This repository contains the official implementation of "FastVLM: Efficient Vision Encoding for Vision Language Models" - CVPR 2025 - apple-aiml-research/ml-fastvlm
- HQ
- Cupertino
- Team size
- 5000+
- Live since
- May 2025
- Founders
- Steve Jobs - Co-founder
- Steve Wozniak - Co-founder
- Ronald Wayne - Co-founder
Some facts above are based on publicly available information and may have changed.
The maker hasn't published a public statement we can verify yet.
Researched with AI · Data refreshed 18 hours ago · How we score
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FastVLM is Apple's open-source vision-language model (CVPR 2025) with a FastViTHD hybrid encoder that cuts vision tokens and time-to-first-token for on-device multimodal inference. It is used by ML engineers and iOS developers building image-understanding features into mobile and edge apps.
Who should use
Buyer-fit is derived from approved personas and use-case evidence. Search-volume noise stays labeled separately.
Best-fit workflows
- Quickly identify and describe image content in mobile applications
- Enable real-time image and text interaction functions such as intelligent customer service
- Combine image understanding and language description in educational software
- Generates image captions and visual Q&A responses on an iPhone using the bundled iOS demo and Apple Silicon checkpoints.
- Drafts alt-text and scene descriptions for photos inside a mobile app without sending images to a cloud API.
- Tracks visual state in a customer-support chat by pairing FastVLM with a 7B LLM for image-plus-text replies.
Pricing reality
Vendor stated
Open-source repository with model weights and code; no listed license fee on the page.
Actual cost
Cost is engineering time plus any Apple Developer program fees and hardware (Apple Silicon Mac, iPhone) needed to build and test.
Hidden costs
3 hidden cost warnings — unlock to view
Pricing reality
Last updated Oct 2026
Starting price
From $ 4 USD
Free tier available.
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Git Large File Storage
$5 per month for 50 GB bandwidth and 50 GB of storage.
$5/mo
$ 4 USD per user/month
$ 4 USD
$ 4 USD per user/month for the first 12 months*
$ 4 USD
$ 21 USD per user/month
$ 21 USD
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LIVE ESTIMATEEstimated spend
$12Recurring billing is usually the real cost driver, not the first-month sticker price.
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Engagement signals (30d)
Based on 6 linked public signals.
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Data sources
Traffic & search proof
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Latest traffic snapshot
Monthly visits
645.5M
Avg visit duration
--
Pages per visit
--
Bounce rate
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Traffic trend
Month-by-month visits from linked public traffic evidence.
Geography
Top regions
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Traffic sources
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FAQ
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Sources and methodology
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