selfhoster11 3 days ago

DDR3 workstation here - R1 generates at 1 token per second. In practice, this means that for complex queries, the speed of replying is closer to an email response than a chat message, but this is acceptable to me for confidential queries or queries where I need the model to be steerable. I can always hit the R1 API from a provider instead, if I want to.

Given that R1 uses 37B active parameters (compared to 32B for K2), K2 should be slightly faster than that - around 1.15 tokens/second.

  • CamperBob2 2 days ago

    That's pretty good. Are you running the real 600B+ parameter R1, or a distill, though?

    • selfhoster11 13 hours ago

      The full thing, 671B. It loses some intelligence at 1.5 bit quantisation, but it's acceptable. I could actually go for around 3 bits if I max out my RAM, but I haven't done that yet.

      • apitman 11 hours ago

        I've seen people say the models get more erratic at higher (lower?) quantization levels. What's your experience been?

    • [removed] 2 days ago
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