Comment by cmrdporcupine
6 hours ago
I tried the FP8 in vLLM on my Spark and although it fit in memory, I started swapping once I actually tried to run any queries, and, yeah, could not have a context larger than 8k.
I figured out later this is because vLLM apparently de-quantizes to BF16 at runtime, so pointless to run the FP8?
I get about 30-35 tok/second using llama.cpp and a 4-bit quant. And a 200+k context, using only 50GB of RAM.
Running llama.cpp rather than vLLM, it's happy enough to run the FP8 variant with 200k+ context using about 90GB vram
yeah, what did you get for tok/sec there though? Memory bandwidth is the limitation with these devices. With 4 bit I didn't get over 35-39 tok/sec, and averaged more like 30 when doing actual tool use with opencode. I can't imagine fp8 being faster.