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QuantaMind

Can your local model actually run an agent? Test it - OSS.

Open-source desktop App that tells you whether a local model can actually run your coding agent, before you waste days finding out it can't. It runs the real agent loop on your own hardware, fully offline, and returns a Ready - Not Ready verdict per model and quant. Public benchmarks don't test your GPU, your VRAM, your quantization, a model that scores well can still hallucinate "done" at step 7. Open source. Works with Ollama, llama.cpp, and MLX.

Top comment

Hey PH 👋 I built QuantaMind because I kept getting burned by local models that looked great on paper and fell apart the moment I put them in an agent loop. The pattern was always the same: a model scores well on some public leaderboard, I load it locally, and then it quietly breaks, a malformed tool call at step 7, or worse, it says "task complete" when nothing got done. Public benchmarks test the model in the cloud. They don't test your GPU, your VRAM, or your quantization, and that combination is exactly what breaks. The question I heard everywhere (and asked myself constantly) was: "I have X GB of unified memory / vRAM, which model actually works?" The honest answer today is a month of trial and error. QuantaMind runs the real agent loop on your own hardware, fully offline, and gives you a Ready / Conditional / Not Ready verdict per model and quant — with the reasons named, never a bare score. It works with Ollama, llama.cpp, and MLX. A few things I care about that shaped it: - It verifies the actual tool calls happened, not the model's claim of "done" — a trivial do-nothing agent scores ~0, not the inflated numbers you see on some benchmarks. - It never fabricates a metric. If something can't be measured on your backend, it says N/A. - It's fully open source and runs entirely on your machine. no prompts or data ever leave. It's early and I'd genuinely love feedback from people running local models day to day. If you've hit the "fits in memory but still fails" wall, I'd love to hear what model/hardware combo burned you, and contributions are very welcome. One thing I'm curious about: what's the smallest quant you've actually trusted in a real agentic workflow?

About QuantaMind on Product Hunt

Can your local model actually run an agent? Test it - OSS.

QuantaMind was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #123 on the daily leaderboard. Open-source desktop App that tells you whether a local model can actually run your coding agent, before you waste days finding out it can't. It runs the real agent loop on your own hardware, fully offline, and returns a Ready - Not Ready verdict per model and quant. Public benchmarks don't test your GPU, your VRAM, your quantization, a model that scores well can still hallucinate "done" at step 7. Open source. Works with Ollama, llama.cpp, and MLX.

On the analytics side, QuantaMind competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how QuantaMind performed against the three products that launched closest to it on the same day.

Who hunted QuantaMind?

QuantaMind was hunted by QuantaMind. 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 QuantaMind including community comment highlights and product details, visit the product overview.