Easiest solution to deploy multimodal AI to mobile
NexaSDK for Mobile lets developers use the latest multimodal AI models fully on-device on iOS & Android apps with Apple Neural Engine and Snapdragon NPU acceleration. In just 3 lines of code, build chat, multimodal, search, and audio features with no cloud cost, complete privacy, 2x faster speed and 9× better energy efficiency.
Hey Product Hunt — I’m Zack Li, CTO and co-founder of Nexa AI 👋
We built NexaSDK for Mobile after watching too many mobile app development teams hit the same wall: the best AI experiences want to use your users’ real context (notes, photos, docs, in-app data)… but pushing that to the cloud is slow, expensive, and uncomfortable from a privacy standpoint. Going fully on-device is the obvious answer — until you try to ship it across iOS + Android with modern multimodal models.
NexaSDK for Mobile is our “make on-device AI shippable” kit. It lets you run state-of-the-art models locally across text + vision + audio with a single SDK, and it’s designed to use the phone’s NPU (the dedicated AI engine) so you get ~2× faster inference and ~9× better energy efficiency — which matters because battery life is important.
What you can build quickly:
On-device LLM copilots over user data (messages/notes/files) — private by default
Multimodal understanding (what’s on screen / in camera frames) fully offline
Speech recognition for low-latency transcription & voice commands
Plus: no cloud API cost, day-0 model support, and one SDK across iOS/Android
Hey Product Hunt — I’m Zack Li, CTO and co-founder of Nexa AI 👋
We built NexaSDK for Mobile after watching too many mobile app development teams hit the same wall: the best AI experiences want to use your users’ real context (notes, photos, docs, in-app data)… but pushing that to the cloud is slow, expensive, and uncomfortable from a privacy standpoint. Going fully on-device is the obvious answer — until you try to ship it across iOS + Android with modern multimodal models.
NexaSDK for Mobile is our “make on-device AI shippable” kit. It lets you run state-of-the-art models locally across text + vision + audio with a single SDK, and it’s designed to use the phone’s NPU (the dedicated AI engine) so you get ~2× faster inference and ~9× better energy efficiency — which matters because battery life is important.
What you can build quickly:
On-device LLM copilots over user data (messages/notes/files) — private by default
Multimodal understanding (what’s on screen / in camera frames) fully offline
Speech recognition for low-latency transcription & voice commands
Plus: no cloud API cost, day-0 model support, and one SDK across iOS/Android
Try today at: https://sdk.nexa.ai/mobile, I’d love your real feedback:
What’s the first on-device feature you’d ship if it was easy?
What’s your biggest blocker today — model support, UX patterns, or performance/battery?