PocketLLM bundles an LLM runtime, model weights, and chat UI on a USB drive. Plug it into any Mac or Linux machine, run one command, and get a local AI no install, no cloud, no trace. Unplug and nothing remains on the host.
Hey Product Hunt! I'm Vraj, a new grad CS student, and I built PocketLLM because I was frustrated with one thing: every time I set up a local LLM, it ate 5–10GB of my SSD — and I had to redo it on every machine.
So I asked: what if the AI just lived on a USB stick?
PocketLLM bundles everything on a single drive. Plug it in, run one command, and you have a local AI chatbot. No install. No cloud. Unplug and nothing remains on the host machine.
The part I'm most proud of: I benchmarked USB vs SSD and found that after the initial model load, inference speed is identical 54 tokens/sec on both. The USB's only penalty is a ~30 second cold start on first chat. After that, it's all RAM.
It's fully open source, works with any Ollama model, and runs on macOS and Linux. I'd love to hear what you think and if you try it, let me know what models you run on it!
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About PocketLLM on Product Hunt
“Your AI runs from a USB stick. Plug in. Chat. Unplug. Gone.”
PocketLLM was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #64 on the daily leaderboard. PocketLLM bundles an LLM runtime, model weights, and chat UI on a USB drive. Plug it into any Mac or Linux machine, run one command, and get a local AI no install, no cloud, no trace. Unplug and nothing remains on the host.
PocketLLM was featured in Hardware (11.4k followers), Artificial Intelligence (466.2k followers), GitHub (41.2k followers) and Tech (621.5k followers) on Product Hunt. Together, these topics include over 270.5k products, making this a competitive space to launch in.
Who hunted PocketLLM?
PocketLLM was hunted by Patel Vraj. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how PocketLLM stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Patel Vraj
Hey Product Hunt! I'm Vraj, a new grad CS student, and I built PocketLLM because I was frustrated with one thing: every time I set up a local LLM, it ate 5–10GB of my SSD — and I had to redo it on every machine.
So I asked: what if the AI just lived on a USB stick?
PocketLLM bundles everything on a single drive. Plug it in, run one command, and you have a local AI chatbot. No install. No cloud. Unplug and nothing remains on the host machine.
The part I'm most proud of: I benchmarked USB vs SSD and found that after the initial model load, inference speed is identical 54 tokens/sec on both. The USB's only penalty is a ~30 second cold start on first chat. After that, it's all RAM.
It's fully open source, works with any Ollama model, and runs on macOS and Linux. I'd love to hear what you think and if you try it, let me know what models you run on it!
GitHub: https://github.com/vraj00222/poc...
website: https://pocketllm-site.vercel.app/