Qualcomm
26 updates on Qualcomm.
Quant.npu runs 4-bit LLMs up to 15.1 percent faster on a Qualcomm NPU
Eight authors report a fully static integer quantisation method that runs 4-bit models up to 15.1 percent faster on a Qualcomm SM8650 NPU.
ShadowNPU scores attention on the Snapdragon NPU and reports 4.5 times faster inference
Peking University and BUPT move attention token scoring onto a Snapdragon NPU and report up to 4.5 times faster inference using a single CPU core.
Google's ML Drift runs Llama 3.1 8B on a phone GPU at 12.7 tokens per second
The paper measures 37.1 decode tokens per second for Gemma2 2B and 12.7 for Llama 3.1 8B on the Adreno 750 GPU of a Samsung S24.
Meta releases Llama 3.2 1B and 3B for phones and edge devices
The two lightweight models carry a 128K context window, were pruned and distilled from Llama 3.1, and shipped with day-one Qualcomm and MediaTek support.
ElastiLM resizes a shared phone LLM per request and switches in 0.31 seconds
Peking University and BUPT built an on-device LLM service that fits model and prompt to each request, switching sub-models in 0.31 seconds.
llm.npu prefills 1,106 tok/s for Qwen1.5-1.8B on a Snapdragon 8 Gen 3
Peking University and BUPT move prompt processing onto the Hexagon NPU and report up to 43.6x faster prefill and up to 59.5x lower energy use.
BUPT measures 22 LLMs on four Android phones at about 200 ms per token
A BUPT team ran 22 models from 0.5B to 7B on four Android phones with llama.cpp and found 7B models take about 4 GB and 200 ms per token.
PowerInfer-2 runs a 47B model on a OnePlus 12 at 11.68 tokens per second
Shanghai Jiao Tong University researchers report a 47B model decoding at 11.68 tokens per second on a OnePlus 12, with weights streamed from flash.
ExecuTorch alpha runs Llama 2 7B on iPhone 15 Pro and Galaxy phones
PyTorch's edge runtime brought 4-bit Llama 2 7B to iPhone and Galaxy handsets, added early Llama 3 8B support and leaned on Apple, Arm and Qualcomm.
Qualcomm AI Hub opens 75 pre-optimised models and profiling on hosted Snapdragon phones
Qualcomm opened a library of more than 75 models tuned for Snapdragon, with compilation and profiling on real phones in its cloud and two 7B chat models listed.
Snapdragon 8 Gen 3 targets 10-billion-parameter models on device
Qualcomm says the new flagship runs generative models with up to 10 billion parameters on device and reaches up to 20 tokens per second for LLMs.
Qualcomm argues for hybrid AI, citing 10 times the cost per generative AI search query
Qualcomm argues that cloud-only inference cannot scale, and puts models of 1B to 10B parameters on phones and laptops at INT4.