BrainChip Announces Sequora Processor IP for Running Generative AI and LLMs on Battery-Powered Edge Devices
BrainChip unveiled Sequora, a processor IP optimized for State Space Models to enable local execution of large language models on battery-powered edge devices with constant memory requirements.
US-based semiconductor IP company BrainChip announced the launch of its 'Sequora' processor intellectual property (IP) core on October 28, 2026. The IP is designed to directly execute generative AI and Large Language Model (LLM) tasks on battery-powered edge devices, such as earphones and sensor nodes.
A key technical feature of Sequora is its optimization for State Space Models (SSMs). Unlike traditional Transformer architectures where memory requirements scale with sequence length, SSMs represent input history with a fixed-size state. This allows Sequora to maintain constant memory usage regardless of sequence length, making it suitable for resource-constrained edge computing scenarios.
BrainChip stated that Sequora complements its existing Akida neuromorphic processor IP: Akida handles streaming sensor data like vibration, audio, and radar, while Sequora manages on-device LLM inference, voice-to-voice dialogue, and AI agent tasks. Sequora uses a shared multiply-accumulate (MAC) array for both signal processing and neural network operations, eliminating the need for a separate DSP preprocessing stage, and supports software updates for new algorithms.
Sequora is currently available as licensable semiconductor IP, provided in fully synthesizable RTL format along with verification IP, synthesis scripts, and a Software Development Kit (SDK). This release marks a recent development in specialized edge AI chip IPs addressing the challenges of localizing large model deployment.