[searealist]

No one will ever derive any utility from running models at this speed. Please prove me wrong. Give me the number of tokens input and output (and dont forget about reasoning) and acceptable time to wait for it and the use case.

[dannyw]

The OpenAI and Anthropic batch APIs give you a 50% discount.

This is like 98%.

[searealist]

I'm not aware of any service that gives you a 98% discount and is served off of M1s. Did you do the math for what this would cost vs K3 on openrouter?

[zozbot234]

antirez's own video (the one I referenced in my comment) shows K3 inference running on M5 Max, not M1-series silicon (which is OP). M1 series has far lower SSD read throughput and memory bandwidth, and can barely fit the model weights on its maxed out internal storage (2TB). (This is why the linked OP resorts to streaming the sparse parameters from the network which is incredibly slow.)

[searealist]

My answer doesn't change if it is M5s. Where is the math showing a 98% discount over K3 on openrouter. Heck, where is the math showing it is any % cheaper? How much electricity will your M5 sip to hit 1M input and 1M output tokens that would cost $3 + $15 there? I bet it is more expensive on the Mac.

[dannyw]

I just mean in terms of incremental inference cost.

If you already committed to your hardware, huge models at single or sub-digit TPS are still useful. LLM-as-judge is a good use case.

If your machine is gonna be idle overnight (and the power efficiency is excellent here), why pay openrouter if it’s not an interactive workload?

[searealist]

Because it's probably still more expensive in electricity costs compared to openrouter. Certainly it's not 98% cheaper.