Can't answer for an RTX 5090, but for an RTX 5080 16GB of RAM (desktop), I get about 6 tokens/sec after some tweaking (f16->q4_0). Kind of on the borderline of usable.. probably realistically need either a 5090 with more RAM or something like a Mac with a unified memory architecture.
A Mac is not going to be all that much faster than a 5080 with any models, other than the ones you can’t currently run at all because you don’t have enough GPU+CPU memory combined.
You’re much better off adding a second GPU if you’ve already got a PC you’re using.
I set this up today on my 5090 at Q6_K quantization and Q4_0 KV, got 50 tokens/s consistently at 123k context, using ~28/32gb vram through LM Studio.
Wow, that sounds usable. I know it's anecdotal but how did you find the quality of the output, and can you compare it to any closed source model?
Not that you asked but I’m getting ~20 tokens/s on my DGX Spark (Asus actually) using an Int4 AutoRound quant, MTP 1 and some other tricks
Can't answer for an RTX 5090, but for an RTX 5080 16GB of RAM (desktop), I get about 6 tokens/sec after some tweaking (f16->q4_0). Kind of on the borderline of usable.. probably realistically need either a 5090 with more RAM or something like a Mac with a unified memory architecture.
My M5 Pro is getting ~11 tokens per second via OMLX for an 8 bit quant.
A Mac is not going to be all that much faster than a 5080 with any models, other than the ones you can’t currently run at all because you don’t have enough GPU+CPU memory combined.
You’re much better off adding a second GPU if you’ve already got a PC you’re using.