https://griptonite.io/ my gym uses this, qr/nfc on routes with ability to take video and it shows you as stick man and where weight is etc. its new but seems good!
I’m keen to understand speed here etc etc. if I bought a Mac studio with 96GB - what can I realistically run, how’s it compare to fable/opus etc and how fast is it?
Currently maxing out two Claude code accounts every x hours when working on large code migrations or setting up new iOS apps etc - most of time it’s fine but occasionally it’s mega frustrating!
I strongly recommend trying LM Studio - it's the lowest friction way to try out models, you can browse https://lmstudio.ai/models and click "Get" and then "Run in LM Studio" to download and run a model.
With 96GB I'd start with the Gemma 4 and Qwen 3.6 models. Any of those should work fine.
I think currently you can only get the M3 Ultra Studio with 96gb, and for coding tasks, say you rub Qwen Coder on it (which doesn't need that much ram), it's not the fastest, something like 30-40 tok/sec. Probably better with a MacBook Pro with the M5 chip. There is a website for comparing different configurations and models: https://llmcheck.net/benchmarks
We never did it - started but changes were too hard to manage on the large code base - we have L4 running on PHP 8.1/Mysql 8 and all is good currently!
I have a Wifi 6E router, so I wonder if 6GHz vs 5 vs 2.4 acts noticeabley differently here? Is the overall shape the same or does the frequency make a big difference?
The thing I’m keen for is keeping my open ai function definitions and having Claude (or Llama) return the same “do this function call with these arguments” syntax. Needs a little prompting to do it but by hand it works just need a wrapper so I can talk to Claude with same inputs as functions as Open AI. Does this do that?
I was in same boat, switched years ago. One thing to be aware of is that on newer M series chips (M1, M2) these are ARM, so if you really really need prod to match then that might be an issue.
On the other hand, we are generally deploying to AWS Graviton anyway which is ARM as well, so perhaps it will be more similar!
I tried this out using ship try. I'm not a python dev, so installed pip and Jupyter, then tried the ticket tagging one and the audio transcripts one, but neither worked - one referenced a json file of ticket examples that didn't exist, and the audio one couldn't import utils.
Not a python person, so not sure if this is me or not, but just very unclear what this is doing/what it's meant to do.
Idea sounds useful, but I can't tell what this is meant to do/what I can do with this.
No pricing also means that hard to understand if this is something I can use in production or not.
I'm usually a typescript/lambda kinda guy for reference, and have already used openai in production on that stack.
Really appreciate you giving it a go in the face of those errors.
In retrospect, that initial `ship try` CLI & those initial packages had too many moving parts for a first launch.
Part of what we're trying to do with this Prompt API template is strip things down to bare bones so that we can nail the basic "clone -> modify -> deploy" flow before layering back on bells & whistles.
If you're ever up for another go, give us a holler and we'll jump in if you hit snags like that again!
