on-device AI

Perplexity's Mac app now supports Hybrid Compute, which starts tasks in the cloud and shifts sensitive steps to a local model running on-device. The feature requires Apple silicon with at least 24GB of unified memory and uses an open-sourced on-device PII classifier to mask private data before any cloud processing.

Liquid AI released DSpark draft model checkpoints for three LFM2.5 models, enabling speculative decoding that speeds up inference by up to 3.18x on H100 GPUs and 2.87x on-device, with day-one support for llama.cpp and SGLang.

Liquid AI has released LFM2.5-VL-3B, a multimodal upgrade to its LFM2-VL-3B model built for on-device grounding, object detection, and document OCR. The model runs at 228 tokens/sec on an Apple M5 Max and 116 tokens/sec on an AMD Ryzen AI Max+ 395, using under 3.3 GB of memory.

Meta released Muse Glimmer, a 30-billion parameter open-weight model under Apache 2.0 license designed to run AI agents locally on consumer hardware. It's an open version of Meta's closed Muse Spark model and supports text, images, and over 100 languages.

Meta CEO Mark Zuckerberg announced the company will open-source its Muse Spark 1.2 model and launch a new on-device model family called Muse Glimmer. The move positions Meta against closed-model rivals OpenAI and Anthropic and against Chinese open-weight labs like DeepSeek and Alibaba.

Liquid AI has released LFM2.5-2.6B, a 2.6B-parameter model trained on 34 trillion tokens with a 128K context window, built for on-device agentic workloads. The company claims it is competitive with models four times its size on tool use and instruction following.

Liquid AI has released LFM2.5-2.6B, a 2.6B-parameter model designed to run capable tool-calling agents locally on laptops and phones. The company claims it matches or beats models up to 4x its size on instruction-following and tool-use benchmarks while running under 2.5GB of memory.

Samsung's Galaxy Z Fold 8, Fold 8 Ultra, and Flip 8 are the first devices to ship with Google's Gemini Nano 4 on-device model and the new Gemini Intelligence feature tier. The launch comes with strict hardware requirements including 12GB+ RAM and qualified system-on-chips.

Adobe is testing AI-powered photo editing features in its experimental Project Indigo camera app for iPhone. The AI Playground, available to a small percentage of users for a limited time, includes object removal, style transfers, photo critiques, and custom prompt-based editing powered by Google's Nano Banana model.

Scam.ai announced a partnership with Qualcomm and launched Halo, an on-device deepfake detection model for live video calls. The announcements were made at Computex 2026 in Taipei, where Scam.ai was featured at Qualcomm's booth.

Apple announced five third-generation foundation models at WWDC26, headlined by AFM 3 Core Advanced—a 20-billion-parameter sparse model that runs on-device by activating only 1-4 billion parameters at a time. For the first time, Apple extended Private Cloud Compute to third-party infrastructure, with AFM 3 Cloud Pro running on Nvidia GPUs in Google Cloud.

Google DeepMind has released quantization-aware training (QAT) optimized versions of its Gemma 4 model family in GGUF Q4_0 format. The QAT versions preserve similar quality to bfloat16 while dramatically reducing memory requirements, with models available across the entire Gemma 4 lineup: E2B, E4B, 12B, 26B A4B, and 31B.

Google launched AI Edge Gallery for macOS, allowing Mac users to run Google's Gemma models locally. The platform ships with five Gemma models, including the newly released Gemma 4 12B—a 12-billion-parameter multimodal model that handles text, vision, and audio while running on consumer laptops with 16GB of RAM.

Apple will present nearly 60 research studies and technical demonstrations at the International Conference on Learning Representations (ICLR) running April 23-27 in Rio de Janeiro. Demos include the SHARP model that reconstructs photorealistic 3D scenes from a single image in under one second, running on iPad Pro with M5 chip.