LattePanda Launches Sigma 2 SBC: Claims Local 35B LLM Capability
LattePanda releases a new single-board computer claiming to run 35B-class quantized large language models locally with 180 TOPS of compute and 64GB RAM.
Chinese hardware company LattePanda announced the "LattePanda Sigma 2," a new x86 single-board computer (SBC), on October 22. Based on the Intel Panther Lake generation Core Ultra X7 358H processor, the company states that its combined CPU, GPU, and NPU deliver up to 180 TOPS (INT8) of AI performance.
To support local large language model execution, the board features up to 64GB of LPDDR5X-8533 memory, with up to 59GB allocatable as VRAM for the GPU/NPU. LattePanda claims this configuration can accommodate 35B-class quantized MoE models and the KV cache required for long contexts. According to vendor self-testing, using INT4 quantization and the OpenVINO framework, the device can run the Qwen3.6-35B-A3B model at approximately 30 tokens per second.
Additionally, the Sigma 2 integrates an RP2350 microcontroller, allowing real-time control of sensors and actuators via GPIO, suitable for robotics or embedded AI applications. The product is currently in pre-order phase at $2,599, with the price set to rise to $2,799 after the pre-order period ends in mid-November.