When Muse models first started coming out I was pretty excited that Meta models were competitive again based on the benchmarks but after trying them out it feels like Meta is making benchmaxxed models that are exciting on bench cards but not really useful in real world scenarios.
To me that is the main problem with Muse models whether it's Spark, Wonder or Ember. While it reads as frontier on benchmarks it really isn't.
This is evident when you compare Dots and Muse the products as well. The model quality is clearly still far behind.
Spark was my go-to at work (technical writing and docs site) on a Cursor API plan for a few weeks because of its speed and price. I was happy with it and recommended it. Now sufficiently outclassed by Haiku 5.5 for tasks of that size.
To me Fable's role was always as a planner or plan reviewer, rather than something individuals or organizations would use as the primary driver. In that case, I think these improvements seem worthwhile in exchange for the cost? Ideally in that role, you want the best performing model.
Not sure if the current rise means it's cost prohibitive to use in that form too.
Considering tokenmaxxing is over and budgets are getting tightened everywhere, what's the use case for fable? Who will use it? Possibly FAANG? Or firms like Apple who have 200 $ per day budget
I’ll use it if there’s a complex bug I need solving quickly, or to weigh in on architectural decisions across large multi-plan projects. It’s a tool to reach for but makes no sense as a daily driver.
To me that is the main problem with Muse models whether it's Spark, Wonder or Ember. While it reads as frontier on benchmarks it really isn't.
This is evident when you compare Dots and Muse the products as well. The model quality is clearly still far behind.
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