Comment by tedsanders
16 hours ago
> Do you then recommend Sol for technical documentation?
I don't know, to be honest. Technical documentation is such a multidimensional skill, and I also don't know your budget. I'd imagine Terra might have the most readable prose, but Astra might be more likely to catch bugs or mistakes to highlight. If the documentation is about a more esoteric language or situation, Astra might have a greater edge than if it's a common language or situation. If you have a long list of documentation guidelines, that might also give more of an edge to Astra. I wouldn't want to make a recommendation without doing a lot of testing, and I haven't done a lot of testing.
Some food for thought, if someone from oAI can't make a direct recommendation for something as direct as "Technical documentation is such a multidimensional skill" - how could we know assess what model to use?
To elaborate, I can ask each model to write a doc about something I know well and tell you which output I like better.
But to assess whether my preference on my problem is going to generalize across other people, other programming languages, other documentation types/formats, etc., and then analyze statistical significance is a thornier question that I don't have the data to answer. I'd rather make no recommendation than a weakly informed recommendation.
I use Astra 6 Extra High for everything.
It’s overkill most of the time, but frankly all these models are “cheap”, and I’d rather waste compute than brain cycles trying to discern which dials are best for each individual as-hoc query.
How are they cheap? Does your organization offer unlimited spend, or does your subscription not run into the same limits as mine?
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But Astra is simply bad at writing. I have to use Argon to rewrite everything Astra wrote in an academic setting. Astra always tries to cover every small detail and engages in defensive writing that is unreadable.
Totally agree. I'm working a lot faster when being just about everything I want on the first hop, without model switching and goofing around to find the sweet spot. When I need a janky answer I run a model locally with llama.cpp
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