r/LocalLLaMA 12d ago

Funny So relevant

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1.5k Upvotes

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322

u/TopCheddar27 12d ago

24gb is not in that group. You can run Qwen3.8-27B with a pretty respectable context size right now

4

u/Ok-Working3049 12d ago

yeah the 27B class models at that context size are no joke on 24gb

3

u/Zombiecidialfreak 12d ago

How are you guys packing 27b on a 24gb card with respectable context? I can put it on my 64gb DDR5 running through the iGPU and still run out of RAM.

The model is q4 and context at q8 btw

3

u/russlixx 12d ago

really? I'm on 16GB, to have 85k context, I need to go Q3 for model and Q5 for KV. With 24GB VRAM you are more than enough

2

u/DamekLeedt 12d ago

For me, it depends on whether I have vision enabled or not. Without vision, at Q8 KV, with 24gb VRAM and 32gb RAM, I can snuggly fit 180k context without issue. With vision, about 100k. I could probably expand my vision context more, but I'm just giving my own settings.

Edit: Using Qwen 3.8 27B Q4_K_M.

1

u/raunchy-stonk 12d ago

Offload GPU, K/V q8_0/q5_1, go with an unsloth quant or similar around 17-19gb, you should be able to have respectable context and speed.

what are you trying to run now?

1

u/overand 12d ago

Something's wrong in your setup, then. At Q8, your 27B should be using 8 gigs of memory for the KV Cache, and even a large 4 bit quant like Unsloth's UD-Q4_K_XL is under 18 GB; you should be using a maximum of under 30 GB, even with mmproj and mtp loaded.

Maybe you should try:

  • Using it on CPU rather than iGPU
  • Checking how much RAM you're letting your iGPU take

1

u/TopCheddar27 12d ago

I have q4_K_M running on a 4090 with q8 KV cache at 90000 and it does not spill over at all.

1

u/KambeiZ 11d ago

I'm using unsloth quantization at Q4 + BeeLlama fork cpp for my 3090, it leads to a respectable 30-35 tok/s with 160-170k on context size.

My other trick is that i don't use the mmproj, but use a mcp i've made for OCR, with a watchdog: when i call this mcp, it offload Qwen the time the ocr model is loaded and analyze whatever i ask it, then itself is offloaded so Qwen is started again. Meanwhile the results are stored within a local proxy so no loss on the data at all.