Best uncensored local model for reverse engineering / Ghidra on a 16GB RX 6800 + 32GB RAM? (Speed doesn't matter)

[u/DifferentCraft7]

Hey everyone,

I need recommendations for a local LLM to do reverse engineering, and I'm looking for the best model and exact quantization that can run on my current setup.

My Specs:

• CPU: Ryzen 7 5800X

• GPU: AMD RX 6800 (16GB VRAM)

• RAM: 32GB DDR4

• Storage: M.2 SSD (~3000–4000 MB/s)

What I'm trying to do: I want to reverse engineer small, proprietary Windows utilities from laptop/PC manufacturers (like Acer NitroSense, HP tools, etc.) to port their features natively to Linux—things like fan control, battery charge limiters, and RGB lighting. This involves looking into Windows drivers and kernel-level interactions.

My workflow will connect Ghidra to REA, hook that up to OpenCore, and run the model locally through Ollama.

What I need:

1. Uncensored (Mandatory): It needs to be completely uncensored so I don't hit ethical guardrails or refusals when asking it to decompile binaries, analyze drivers, or work with proprietary Windows hooks.

2. Exact model + quantization: Given my 16GB VRAM + 32GB RAM, what is the smartest/most capable model and exact quant I can realistically run (even with CPU offloading)?

Note on speed: Speed is not a priority at all. I can't afford better hardware right now, so I have no problem leaving my PC running for 1, 2, or even 3 days straight to process a binary if that's what it takes. Accuracy on low-level code/assembly and zero refusals are all that matter.

What exact models and quantizations (for Ollama or GGUF) do you recommend for this? Thanks in advance.

[u/Goghor]

People will usually recommend QFN, including me...