It's less than you'd think. I'm using the 35B-A3B model on an A5000, which is something like a slightly faster 3080 with 24GB VRAM. I'm able to fit the entire Q4 model in memory with 128K context (and I think I would probably be able to do 256K since I still have like 4GB of VRAM free). The prompt processing is something like 1K tokens/second and generates around 100 tokens/second. Plenty fast for agentic use via Opencode.

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rahimnathwani 5 hours ago | parent | next [-]

There seem to be a lot of different Q4s of this model: https://www.reddit.com/r/LocalLLaMA/s/kHUnFWZXom

I'm curious which one you're using.

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suprjami 5 hours ago | parent [-]

Unsloth Dynamic. Don't bother with anything else.

	▲	rahimnathwani 5 hours ago \| parent [-]
		UD-Q4_K_XL?

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msuniverse2026 5 hours ago | parent | prev [-]

I've had an AMD card for the last 5 years, so I kinda just tuned out of local LLM releases because AMD seemed to abandon rocm for my card (6900xt) - Is AMD capable of anything these days?

	▲	pja 4 hours ago \| parent \| next [-]
		> I've had an AMD card for the last 5 years, so I kinda just tuned out of local LLM releases because AMD seemed to abandon rocm for my card (6900xt) - Is AMD capable of anything these days? Sure. Llama.cpp will happily run these kinds of LLMs using either HIP or Vulcan. Vulkan is easier to get going using the Mesa OSS drivers under Linux, HIP might give you slightly better performance.
	▲	wirybeige 5 hours ago \| parent \| prev [-]
		The vulkan backend for llama.cpp isn't that far behind rocm for pp and tp speeds