Samsung taps Nota AI to optimize Exynos 2600 on‑device models

This Samsung–Nota AI tie-up is a microcosm of a bigger shift: advanced language and vision models are no longer just cloud workloads, they’re becoming standard features of flagship phones. By baking NetsPresso into the Exynos 2600 toolchain, Samsung is effectively betting that Galaxy devices will run sizable generative models locally — for translation, summarization, agents and more — instead of round‑tripping every query to the data center.([ajupress.com](https://www.ajupress.com/view/20251230084044411))

Strategically, that matters for the race to AGI because it broadens who can experiment with agentic and multimodal interfaces at low marginal cost. If hundreds of millions of devices can host trimmed but capable models with good latency and privacy, you get a much richer stream of real‑world usage data and edge‑case behavior to learn from. That feedback loop can feed back into larger frontier models and agent systems running in the cloud.

The partnership also illustrates a short‑term reality for smaller AI companies: one path to relevance is not building your own frontier model, but owning the optimization stack that lets everyone else’s models run on constrained hardware. If Nota can establish itself as the default compression layer for Exynos, it gains leverage in future negotiations — and might become an acquisition target for chipmakers or platform giants looking to own more of the on‑device AI stack.