71–80 of 180 posts
Unfortunately, I found the small context window makes the utility pretty limited.
apfel -o json "Translate to German: apple" | jq .content
I like the approach of running everything locally. I'm strongly of the opinion that the privacy angle for local models is going to keep getting stronger and more relevant. The amount of articles that come out about accidents happening because of people handing too much context to cloud models the more self reinforcing this will become.
local is best for privacy, but i personally think you don't need to go local. anthropic, google, openai etc, decided that their consumer ai plans would not be private. partly to collect training data, the other half to employ moderators to review user activity for safety. we trust that human moderators will not review and flag our icloud docs, onedrive or gmail, or aggregate such documents into training data for llms…
As an enthusiastic reader of books like Privacy is Power and Surveillance Capitalism, it feels good to have a private tool that is ready at hand.
Is this for Tahoe only? I’m still clutching onto Sequoia
Earlier quoted context omitted.
local is best for privacy, but i personally think you don't need to go local. anthropic, google, openai etc, decided that their consumer ai plans would not be private. partly to collect training data, the other half to employ moderators to review user activity for safety. we trust that human moderators will not review and flag our icloud docs, onedrive or gmail, or aggregate such documents into training data for llms…
> i personally think you don't need to go local. I personally think everyone should default to using local resources. Cloud resources should only be used for expansion and be relatively bursty rather than the default.
The task is basically predicting pricing and costs.
Apple’s model came out on top—best accuracy in 6 out of 10 cases in the backtest. That surprised me.
It also looks like it might be fast enough to take over the whole job. If I ran this on Sonnet, we’re talking thousands per month. With DeepSeek, it’s more like hundreds.
So far, the other local models I’ve tried on my 64GB M4 Max Studio haven’t been viable - either far too slow or not accurate enough. That said, I haven’t tested a huge range yet.
Is this for Tahoe only? I’m still clutching onto Sequoia
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Referenced from: /opt/homebrew/Cellar/apfel/0.6.25/bin/apfel (built for macOS 26.0 which is newer than running OS)
Reason: tried: '/System/Library/Frameworks/FoundationModels.framework/Versions/A/FoundationModels' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/System/Library/Frameworks/FoundationModels.framework/Versions/A/FoundationModels' (no such file), '/System/Library/Frameworks/FoundationModels.framework/Versions/A/FoundationModels' (no such file, not in dyld cache)