Developer tools
22 updates on Developer tools.
Google adds local model support to the Antigravity SDK with Gemma 4 on LiteRT
Antigravity agents can now run on Gemma 4 26B A4B through LiteRT, with Google recommending more than 24 GB of VRAM or unified memory.
Qualcomm positions Snapdragon X2 as an agentic PC chip and previews Linux support
Qualcomm says its Snapdragon X2 platform now delivers up to 85 TOPS and up to twice the tokens per second of the first-generation X Elite for on-device AI agents.
vivo previews BlueCode phone coding agent and researches a 30B MoE on-device model
vivo showed a preview of BlueCode, a native coding agent for phones, and says it is researching a 30B-parameter BlueLM MoE model for on-device use.
ASUS announces Ascent QN10, a mini PC with Snapdragon X2 Elite and an 80 TOPS NPU
The Ascent QN10 is a mini PC under 0.7 liters with an 18-core Snapdragon X2 Elite and a Hexagon NPU rated at up to 80 TOPS for local LLM inferencing.
Desert Ant Labs releases 18 on-device models for speech, audio and privacy tasks
Desert Ant Labs released 18 single-task models that run locally on phones and laptops and are free up to 100k monthly active devices.
Gemini Nano 4 ships on Samsung foldables with ML Kit Prompt API access
Google says Samsung’s new foldables carry Gemini Nano 4 with support for more than 140 languages, reachable from apps through ML Kit’s Prompt API.
Apple ships Python bindings for the on-device Foundation Models framework
The apple-fm-sdk package calls the on-device Apple Intelligence model from Python on macOS 26, for scripting and batch evaluation outside Swift.
ExecuTorch 1.0 reaches general availability for on-device PyTorch models
The PyTorch edge runtime promotes Core ML, Qualcomm Hexagon, Arm Ethos-U, Vulkan and XNNPACK backends to production status.
lm-Meter times on-device inference and finds prefill, not decode, is the bottleneck
A profiler that runs inside the phone measures each inference phase and reports prefill slowing 158 times as models grow, against 10 times for decode.
Apple opens its on-device model to all apps with the Foundation Models framework
Any app can call the roughly 3-billion-parameter on-device model from Swift, offline and free of charge, with guided generation and tool calling.
Flower Intelligence runs models on device, with remote handoff off by default
Flower Labs released a preview library that runs Llama 3.2 and SmolLM2 locally via WebLLM or MLX Swift, and calls its remote service only if an app enables it.
Meta ships Llama Stack with Swift and Kotlin clients for on-device inference
Meta standardised its Llama APIs so mobile apps can swap a cloud endpoint for an on-device ExecuTorch runtime without changing the calling code.