At 1t/s it's still faster than humans for a lot of tasks, basically doing overnight what could take humans half a week. Plus you can always parallelize.
Frontier models are amazing, but what will really be useful for us is having models and hardware so efficient that you can run useful LLMs locally. One of my favourite LLMs to this day is still my jail-broken gemma4 12b because it's small enough to run on my computer, but also 100% local and free as in liberty.
Which tasks? I think you're underestimating how token hungry current proposed workflows are.
You said it would do overnight what would take a human half a week, so I'm curious what tasks you are doing where AI is 3x faster than you even at 1t/s
I don't think it's valuable at all to try and craft a specific prompt to "one-shot" a task, I'm way faster just doing small asks and guiding it. At 1t/s, how would you even know your prompt was insufficient? It would take you 7 hours to see it.
- list of many endpoints with the JSON they receive and return and description of what they need to achieve
Stuff you could probably do in a single work day if you lock in and enter flow state, but in a typical job takes like half a week. And the vast majority of times the AI one shots it with no bugs, where I would have copy paste errors or dumb stuff I'd need to fix before it's shippable.
I get weird interruptions. I can only guess its related to some kind of timeouts in the harness or something.
Its not a problem of the model of course, but it seems impractical atm.
I wonder if anyone else had this kind of thing happening.
hermes > pi > opencode ??
or is hermes better in general? habent tried it hermes/pi yet
I ran opencode task again last night since it's slow and this morning i got a "SSE read timed out"
logs show tokens still streaming in steadily (every 3-4s, 46,818 tokens in) right up to the moment opencode disconnected
opencode cut a response that was actively generating (not a stalled one)