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Gargantua
Every deletion explained, every rule yours to edit
Every other Mac cleaner is a black box: a "junk found" number and a Clean button. Gargantua shows its work. Every file traces to a named rule that says why it's safe to remove, and you can read that rule, edit it, or drop in your own YAML, no rebuild. Want more than the rule's reason? An on-device or cloud model can explain any item in depth, but never downgrade a safety rating. Files near system paths stay protected, undeletable by anyone. Open source, local-first, free to build from source.
Yeah, it's another Mac cleaner, I know. And I'm guessing the first reply is "how's this different from [other cleaner]." So let me put the actual difference right up top: every other cleaner asks you to trust a number.
Gargantua shows its work, two ways.
1. The rules are open, and they're yours. Every file it flags comes from a named rule that says exactly why it's safe to remove. You can read that rule, see who reviewed it, edit it, or drop your own YAML rule into a folder and it just loads, no rebuild. The whole ruleset is public. No vendor secret list.
2. It explains itself. Every finding carries a plain reason pulled straight from its rule. Want more depth? It can explain any item further using a small model on your Mac, or your own cloud key. Either way the AI can add detail but can never lower a safety rating. Anything near system files stays protected and can't be deleted, by you or any model.
Everything else (caches, app uninstalls with the leftovers, duplicates, disk treemap, file health) runs through that same trust layer, and there's a local MCP server so any MCP agent can scan and clean under guardrails.
Open source (AGPL), local-first, nothing phones home. Free and fully unlocked if you build from source. The prebuilt app is a 14-day trial, then $19 once for 3 Macs to run deletes. Scans are always free.
brew install --cask inceptyon-labs/tap/gargantua
Apple Silicon, macOS 14+. Ask me anything.
If you run local LLMs or diffusion models, most cleaners treat that as one big folder: find the models dir, delete it, hope you didn't need anything in there.
Trouble is, re-downloading a few GB isn't free, and a blunt folder wipe takes the models you still use along with the junk. Gargantua works at the file level instead. It looks at each .gguf / .safetensors / .onnx / PyTorch weight by name and size (never reads the contents), flags exact duplicates and orphaned files nothing points to anymore, and keeps all of it review-only, because that delete call should be yours, not he app's.
So you reclaim the space that's genuinely wasted without gambling a model you wanted to keep.
About Gargantua on Product Hunt
“Every deletion explained, every rule yours to edit”
Gargantua was submitted on Product Hunt and earned 4 upvotes and 2 comments, placing #160 on the daily leaderboard. Every other Mac cleaner is a black box: a "junk found" number and a Clean button. Gargantua shows its work. Every file traces to a named rule that says why it's safe to remove, and you can read that rule, edit it, or drop in your own YAML, no rebuild. Want more than the rule's reason? An on-device or cloud model can explain any item in depth, but never downgrade a safety rating. Files near system paths stay protected, undeletable by anyone. Open source, local-first, free to build from source.
Gargantua was featured in Mac (103.6k followers), Open Source (68.6k followers), Developer Tools (515.4k followers), GitHub (41.3k followers) and Vercel Day (20 followers) on Product Hunt. Together, these topics include over 122.5k products, making this a competitive space to launch in.
Who hunted Gargantua?
Gargantua was hunted by Jason Newberg. 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 Gargantua stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Jason Newberg