VISION AI THAT RUNS EVERYWHERE

VISION AI THAT RUNS EVERYWHERE

VISION AI THAT RUNS EVERYWHERE

Moondream is the easiest and fastest way to build Vision AI that runs on cloud, on-prem, desktop, mobile, and edge.

Moondream is the easiest and fastest way to build Vision AI that runs on cloud, on-prem, desktop, mobile, and edge.

Moondream is the easiest and fastest way to build Vision AI that runs on cloud, on-prem, desktop, mobile, and edge.

Over 5 million downloads, and trusted by fast-growing companies worldwide

PROMPT-BASED

Powered by state-of-the-art VLM models. Prompt in minutes, no model training required.

RUN EVERYWHERE

One-click distill creates smaller, more efficient models optimized for your target device.

EASY INTEGRATION

Client libraries make it a snap to integrate into Python, Javascript, and beyond. Switch from cloud to local inference with a flag.

Capabilities

Capabilities

Our state of the art models are specialized for specific tasks we call "capabilities".

Our state of the art models are specialized for specific tasks we call "capabilities".

Our state of the art models are specialized for specific tasks we call "capabilities".

VISUAL QUESTION ANSWERING

Powered by state-of-the-art VLM models. Prompt in minutes, no model training required.

OCR

High accuracy text recognition from any type of document: newspapers, books, forms, and even hand-written notes.

COUNTING

Get accurate counts of things from prompts, e.g. “people”, “paperclips”, “trucks”.

CLASSIFICATION

Categorize images based on your predetermined options. “Alligator or Crocodile?” “Is this fruit fresh or rotten?”

What our fans say

What our fans say

More testing of the amazing Moondream open source multimodal LLM today! It is massively small: 1.6B parameter model built using SigLIP, Phi-1.5 and the LLaVA training dataset. I am really impressed. More soon.

Brian Roemmele

@BrianRoemmele

Moondream: a 1.6 Billion parameter model that is quite effective and possibly able to go toe to toe with the bigger models in the future.

MasteringMachines AI

@MstrMachines

MoonDream - A tiny vision language model that performs on par w/ models twice its size by @vikhyatk. Its so fast, you might not even catch it streaming output!

Luis C

@lucataco93

moondream is *wicked* fast.

CJ

@cj_pais

More testing of the amazing Moondream open source multimodal LLM today! It is massively small: 1.6B parameter model built using SigLIP, Phi-1.5 and the LLaVA training dataset. I am really impressed. More soon.

Brian Roemmele

@BrianRoemmele

Moondream: a 1.6 Billion parameter model that is quite effective and possibly able to go toe to toe with the bigger models in the future.

MasteringMachines AI

@MstrMachines

MoonDream - A tiny vision language model that performs on par w/ models twice its size by @vikhyatk. Its so fast, you might not even catch it streaming output!

Luis C

@lucataco93

moondream is *wicked* fast.

CJ

@cj_pais

  • moondream is *wicked* fast.

    CJ

    @cj_pais

  • MoonDream - A tiny vision language model that performs on par w/ models twice its size by @vikhyatk. Its so fast, you might not even catch it streaming output!

    Luis C

    @lucataco93

  • Moondream: a 1.6 Billion parameter model that is quite effective and possibly able to go toe to toe with the bigger models in the future.

    MasteringMachines AI

    @MstrMachines

  • More testing of the amazing Moondream open source multimodal LLM today! It is massively small: 1.6B parameter model built using SigLIP, Phi-1.5 and the LLaVA training dataset. I am really impressed. More soon.

    Brian Roemmele

    @BrianRoemmele

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MOONDREAM © 2024 All rights reserved

Made with 🤍 in Seattle

MOONDREAM

Newsletter

Stay up-to-date with Moondream releases. No spam, ever.

By signing up you agree to our privacy policy

MOONDREAM © 2024 All rights reserved

Made with 🤍 in Seattle

MOONDREAM

Newsletter

Stay up-to-date with Moondream releases. No spam, ever.

By signing up you agree to our privacy policy

MOONDREAM © 2024 All rights reserved

Made with 🤍 in Seattle