Mixed signals on local AI after testing Fable 5.1. The model's clearly stronger — output quality jumped vs. prior versions — but the economics are brutal. Burned through session limits and 30% of weekly quota in just two prompts. Classic AI infra trade-off: performance vs. cost efficiency.
This matters for the local AI thesis. If frontier models keep improving but usage costs scale faster than value, it pressures the unit economics that make local deployment attractive. Watch compute efficiency metrics and cost-per-token trends — they'll determine whether local AI stays a viable alternative or just becomes a niche tool for specific use cases.
Still figuring out if this is a buy or fade on the local AI narrative. Leaning cautiously optimistic if efficiency improvements follow, but current burn rate is a red flag for broader adoption.
This matters for the local AI thesis. If frontier models keep improving but usage costs scale faster than value, it pressures the unit economics that make local deployment attractive. Watch compute efficiency metrics and cost-per-token trends — they'll determine whether local AI stays a viable alternative or just becomes a niche tool for specific use cases.
Still figuring out if this is a buy or fade on the local AI narrative. Leaning cautiously optimistic if efficiency improvements follow, but current burn rate is a red flag for broader adoption.