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Tom
A local Windows AI with its work in view
AI for more of us. Tom brings local Gemma 4 to everyday Windows PCs, with a light harness, visible actions and local file tools. No dedicated GPU required. Built with GPT-6 Astra. Early beta: browsing and complex tasks still need patience.
Hi Product Hunt! I’m Dekker, building Tom at OsbornVentures. I believe in AI for all. To get there, we have to start with the computers people already own and make the experience easier to understand.
Tom’s design target is ordinary Windows PCs from the DDR4 era onward, without making dedicated graphics memory the price of entry. Conservative settings use a small CPU thread budget. The aim is useful local AI on everyday hardware, with Windows integration that feels at home. Physical 8 GB testing is still pending, so this is a design target rather than a promise for every machine.
Gemma 4 brings language, coding and image understanding; Tom adds a lightweight harness to put those abilities to work with local files, programs and visible actions. Nine animated ASCII states, an informative startup checklist, a context ring, expandable activity and offline AI help explain what is happening. Setup asks what Tom should call you, and file results open locally.
Please be patient with Tom! The harness is a work in progress and draws on elements of our recent Eldon harness. Tom can be very useful for focused local tasks, but browsing is not a strong point. Complex code and long tasks still need supervision. Our small release checks passed 5 of 6 focused local tasks and 2 of 5 broader attempted tasks on one 32 GB Windows PC. The public report includes the failures; these are not general reliability scores.
GPT-6 Astra helped me build, test and refine Tom’s app and harness. This is our GPT-6 Astra Challenge entry; Gemma 4 runs locally through llama.cpp when you use Tom. Thank you to the teams behind the stack—credits and licenses are included.
Tom is free, with Apache 2.0 source, one complete full installer and a small network installer. This release is unsigned. The website lists prerequisites and checksums to help you get started.
What everyday task would you want Tom to make easier?
About Tom on Product Hunt
“A local Windows AI with its work in view”
Tom was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #30 on the daily leaderboard. AI for more of us. Tom brings local Gemma 4 to everyday Windows PCs, with a light harness, visible actions and local file tools. No dedicated GPU required. Built with GPT-6 Astra. Early beta: browsing and complex tasks still need patience.
On the analytics side, Tom competes within Artificial Intelligence, GitHub and OpenAI Day — topics that collectively have 520.6k followers on Product Hunt. The dashboard above tracks how Tom performed against the three products that launched closest to it on the same day.
Who hunted Tom?
Tom was hunted by Dekker Osborn. 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.
For a complete overview of Tom including community comment highlights and product details, visit the product overview.
Dekker Osborn
Hi Product Hunt! I’m Dekker, building Tom at OsbornVentures. I believe in AI for all. To get there, we have to start with the computers people already own and make the experience easier to understand.
Tom’s design target is ordinary Windows PCs from the DDR4 era onward, without making dedicated graphics memory the price of entry. Conservative settings use a small CPU thread budget. The aim is useful local AI on everyday hardware, with Windows integration that feels at home. Physical 8 GB testing is still pending, so this is a design target rather than a promise for every machine.
Gemma 4 brings language, coding and image understanding; Tom adds a lightweight harness to put those abilities to work with local files, programs and visible actions. Nine animated ASCII states, an informative startup checklist, a context ring, expandable activity and offline AI help explain what is happening. Setup asks what Tom should call you, and file results open locally.
Please be patient with Tom! The harness is a work in progress and draws on elements of our recent Eldon harness. Tom can be very useful for focused local tasks, but browsing is not a strong point. Complex code and long tasks still need supervision. Our small release checks passed 5 of 6 focused local tasks and 2 of 5 broader attempted tasks on one 32 GB Windows PC. The public report includes the failures; these are not general reliability scores.
GPT-6 Astra helped me build, test and refine Tom’s app and harness. This is our GPT-6 Astra Challenge entry; Gemma 4 runs locally through llama.cpp when you use Tom. Thank you to the teams behind the stack—credits and licenses are included.
Tom is free, with Apache 2.0 source, one complete full installer and a small network installer. This release is unsigned. The website lists prerequisites and checksums to help you get started.
What everyday task would you want Tom to make easier?