Models
Liquid AI releases LFM2.5-24B-A2B, a 2B-active MoE for local agents
Liquid AI reports 184 tok/s on an Apple M5 Max for its 24B-parameter mixture-of-experts model, which activates 2.45B parameters per token.
FunctionGemma 270M fine-tune reaches 76.5% on 15 mobile actions, with an Android demo
Fine-tuning FunctionGemma 270M on 9,500 synthetic mobile-action conversations raises end-to-end accuracy from 29.3% to 76.5%, with a Pixel 8 Pro demo app.
Nvidia releases Nemotron-3-Diarization, a 100M speaker model with 0.32 second latency
Nemotron-3-Diarization labels up to eight speakers in streaming or offline audio and ranks first on Voice Arena’s Diarization-Bench v1 with 14.7% DER.
Liquid AI releases a DSpark drafter that speeds up LFM2.5-VL-3B decoding
Liquid AI’s 280M-parameter draft model speeds up decoding of its 3B vision-language model by up to 3.13x on Apple Silicon, for 8.9% more parameters.
OPPO unveils ColorOS 17 with an on-device linear-attention model and 128K context
OPPO says the on-device model in ColorOS 17 uses linear attention, supports 128K context and needs 48% less memory and 55% less energy than its predecessor.
Cactus releases Needle 3, a 121M-parameter tool-calling model in an 8 to 29 MB binary
Needle 3 is a 121M-parameter model for tool calling, structured extraction and embeddings that ships as a single 8 to 29 MB binary.
Edge0 releases MoE expert-offloading framework, demos 35B model on iPhone
Edge0 streams mixture-of-experts weights from storage. Its 35B tier reports 2.9 GiB peak memory on a Mac mini M4 Pro; a launch post shows a 35B model on an iPhone.
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.
OpenBMB releases MiniCPM5-2B for local deployment
A 2.5-billion-parameter dense model with a 131,072-token context, released under Apache-2.0 with GGUF, MLX and LiteRT-LM builds.
Google lists first Gemini Nano 4 phones, requires Nano 3 for Gemini Intelligence
ML Kit GenAI documentation now names nano-v4 devices and sets Nano v3 or greater, plus 12 GB of RAM, as the requirement for Gemini Intelligence.
Artificial Analysis benchmarks 33 local models on an iPhone 17 Pro
A benchmark of quantised small models on an iPhone 17 Pro reports intelligence scores, generation times and peak memory between 0.4 and 6.9 GB.
Graphcore runs Llama 3.2 11B Vision on a Pixel 8a with 2.7-bit quantisation
Graphcore Research fits Llama-3.2-11B-Vision-Instruct into 3.6 GB with a 2.7-bit format and runs it on a Pixel 8a at 3.8 tok/s.