MOmodinfo·Aug 30, 2025Submission
Moondream – a tiny vision language model that runs anywhere
6 points · Open discussionm87-labs
moondream
Python2023–2025
m87-labs / moondream
moondream
tiny vision language model
5Distinct people
5Mentions
0Explicit recommenders
10.2KGitHub stars
What to know before exploring
What it is
tiny vision language model
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
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Also in these discussions
No other repository is repeatedly linked in the same discussions.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month5 dated mentions
Observed mentions: 2023-12-30 01:49:07 UTC to 2025-08-30 17:10:41 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Dec 2023 | 2023-12-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 1 | 0 |
| Jan 2024 | 2024-01-01 00:00:00 UTC | 2024-02-01 00:00:00 UTC | 1 | 0 | 1 |
| Feb 2024 | 2024-02-01 00:00:00 UTC | 2024-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2024 | 2024-03-01 00:00:00 UTC | 2024-04-01 00:00:00 UTC | 1 | 1 | 0 |
| Apr 2024 | 2024-04-01 00:00:00 UTC | 2024-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2024 | 2024-05-01 00:00:00 UTC | 2024-06-01 00:00:00 UTC | 1 | 0 | 1 |
| Jun 2024 | 2024-06-01 00:00:00 UTC | 2024-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2024 | 2024-07-01 00:00:00 UTC | 2024-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2024 | 2024-08-01 00:00:00 UTC | 2024-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2024 | 2024-09-01 00:00:00 UTC | 2024-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2024 | 2024-10-01 00:00:00 UTC | 2024-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2024 | 2024-11-01 00:00:00 UTC | 2024-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2024 | 2024-12-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2025 | 2025-01-01 00:00:00 UTC | 2025-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2025 | 2025-02-01 00:00:00 UTC | 2025-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2025 | 2025-03-01 00:00:00 UTC | 2025-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2025 | 2025-04-01 00:00:00 UTC | 2025-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2025 | 2025-05-01 00:00:00 UTC | 2025-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2025 | 2025-06-01 00:00:00 UTC | 2025-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2025 | 2025-07-01 00:00:00 UTC | 2025-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2025 | 2025-08-01 00:00:00 UTC | 2025-09-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
5 sourcesThere are advantages to smaller models, namely you can process a lot more data, with a lot less vram. I think the intent here from the Google team is for a task-specific VLM that you fine-tune on your data, rather than a general purpose assistant.
From my own experimentation I have found it to really pack a punch for its weight. Another small model which has been very good has been https://github.com/vikhyat/moondream .
In PaliGemma: Open-Source Multimodal Model by GoogleMoondream: Tiny Vision Language Model
1 points · Open discussionAutomatically take a screenshot and feed it to https://github.com/vikhyat/moondream or similar? Doable. But while very impressive, the results are a bit of mixed bag (some hallucinations)
In Show HN: WhisperFusion – Low-latency conversations with an AI chatbotShow HN: Moondream, a small vision language model that runs on 8GB of RAM
I've been working on training this small vision language model for the last month - excited to release the first prototype today! It is based on SigLIP (image encoder), Phi-1.5 (text model) and trained using the LLaVa-1.5 training dataset.
It runs reasonably fast on CPU with ~8GB of RAM in full 32-bit precision. There's plenty of room to speed it up and reduce memory consumption by quantizing the model.
I posted a video of it running on my M2 Macbook Air (on CPU not MPS, so performance should be comparable on other hardware) on Twitter to demonstrate inference speed: https://twitter.com/vikhyatk/status/1740910503323734448
9 points · Open discussion