Press Space to continue
Press Space to continue
Coinbase CEO @brian_armstrong in June: "My guess is that within 12-18 months, 80% of our workloads will be going toward models that are 99% cheaper." "20% of it will still go to frontier models where you need to be IQ-maxxing." "Open source models are 3-6 months behind the frontier models, but they're 99% cheaper for inference." "So we made some very simple changes, like more intelligent routing of prompts, depending on the complexity of the query, to the right model. We started caching…
Brian Armstrong@brian_armstrong1d ago
We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud prevention in this case). I think we'll see more of this pattern inside companies. The frontier models are amazing generalists. But increasingly you'll see specialist models out perform on more narrow tasks, either working on teams, or by themselves. We're making it easy to fine tune models internally for our employees. We even have a skill for it in our internal harness that makes it easy to spin these up and start training them: "/fine-tune-and-serve-llm I want to fine-tune Qwen for payments risk review. help me get started" I imagine we'll have some backend services that could be replaced entirely by this new architecture.
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