DeepSeek's $10M model narrows the gap with frontier AI labs

DeepSeek V4.1 Flash demonstrates that training a competitive large language model no longer requires the $100M+ budgets that defined the frontier, collapsing the capital moat that protected OpenAI and Anthropic. The MIT license release signals a deliberate strategy to commoditize the model layer itself—forcing incumbent value capture upstream into applications and inference infrastructure, where lock-in is weaker. Competition shifts from "who can train the best model" to "who can build the most defensible products on top of commodity models," moving the battleground to layers where differentiation is harder to replicate.