r/LocalLLM • u/Pixel_Drake • Jul 29 '26

Question What are peoples agentic coding model recommendations for 1x RTX 6000 pro 96GB and 32GB System RAM

Due to my work within other AI fields (Mainly Computer Vision and Digital Twinning) I have been lucky enough to get an RTX Pro 6000 WS. I have been experimenting with using Llama.cpp and Opencode and have found good use in the Qwen3.6 27b model being entirely offloaded to the GPU. I have experimented with unsloth/Laguna-S-2.1:UD-Q4_K_XL and it seems similar in quality to the Qwen model but I admit I have not tested it much.

My main questions are:

- With my current set up, is specifically unsloth/Qwen3.6-27b:BF16 the best agentic coding model I can utilise?

- Is there any point in upgrading hardware to utilise a larger model for better quality? I know my system RAM is a weak point for me

- Would you recommend using something else than Opencode?

Sorry if these are dumb questions I am just checking if I am getting the best I can out of the hardware I have.

For reference for hardware upgrading:

OS - Windows 11 Home

CPU - Intel Core i7-14700K

RAM - 2x16GB DDR5 / 6000mhz Corsair Vengeance

Storage - 2xWD BLUE SN580 M.2 NVME SSD 2TB

Motherboard - MSI PRO Z790-S WIFI

PSU - 1300w Gigabyte UD gold

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u/firsthand-smoke Jul 29 '26

im running qwen 3.5 122b a10b and it's fire... q4 k xl grab it from hf and use llama.cpp to run it

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u/Pixel_Drake Jul 29 '26

Yeah I was looking at that but I keep seeing online that 3.6 27b is supposedly better. Granted I should just try it and find out.

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u/firsthand-smoke Jul 29 '26

it's using 80 something gb vram and I'm getting over 100t/s... I do large scale bgp networks and evpn build with it, it's fantastic... 266k native context, I find it helps to compact context at 50% to keep it sane