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Parthus

Category: AI Chips / Semiconductors

China's first native robotics 'brain chip' company, a Peking University spin-off developing a unified neuromorphic-GPU architecture (BiGPU) for embodied intelligence, targeting replacement of Nvidia Jetson in Chinese robotics. Parthus was founded in 2025. The company is led by 殷积磊 (Yin Jilei). Based in Beijing, China. Team size: 11-50. Total funding raised: $68.6M. Latest round: Seed. Key investors include 中关村资本 (Zhongguancun Capital); 启航投资 (Qihang Investment); 上海未来产业基金 (Shanghai Future Industry Fund); 石溪资本 (Shixi Capital); 佰维存储 (Biwin Storage); 燕创集团 (Yanchuang Group); 海益投资 (Haiyi Investment); 探元创投 (Tanyuan Venture Capital).

Founded
2025
Headquarters
Beijing, China
Team size
11-50
Total funding
$68.6M

Value proposition

First native Chinese robotics 'brain chip' that fuses neuromorphic (brain-inspired) computing with general-purpose GPU compute in a unified architecture (BiGPU), enabling low-power, high-efficiency AI inference for embodied intelligence while maintaining full software compatibility with mainstream AI frameworks.

Products and solutions

BiGPU (Brain-Inspired GPU) architecture — unified neuromorphic-GPU chip for embodied intelligence 'brain'; targets Nvidia Jetson replacement for Chinese robotics market; supports Attention Transformer, VLA, world models, and spiking neural networks

Unique value

Proprietary Brain-Inspired GPU (BiGPU) architecture that homogeneously fuses ANN and SNN computation into a single instruction set and toolchain, eliminating the complexity of heterogeneous solutions while achieving dramatic power reduction for robotics edge AI.

Target customer

Chinese humanoid robotics companies; embodied intelligence OEMs; edge AI and industrial automation providers seeking domestic alternatives to Nvidia Jetson

Industries served

Embodied Intelligence / Humanoid Robotics; Edge AI; Industrial Automation

Technology advantage

Homogeneous fusion of ANN (GPU) and SNN (neuromorphic) computation in a single architecture with shared instruction set and toolchain; converts >80% of GEMM operations from ANN to SNN-style accumulate computation for dramatic power reduction; incubated from Peking University PAICORE Lab with deep neuromorphic research heritage; first-mover in native Chinese robotics 'brain chip' market

How they differentiate

Unlike competitors using heterogeneous (separate SNN + NPU) approaches, Parthus uses a homogeneous fused architecture (BiGPU) that shares a single instruction set and software toolchain, deeply compatible with mainstream AI ecosystems. This reduces development complexity and ecosystem integration costs while achieving the power benefits of neuromorphic computing.

Main competitors

Nvidia Jetson (Jetson AGX Orin / Thor) — dominant incumbent; 天数智芯 (Iluvatar CoreX) with '彤央' (Tongyang) edge AI chips; SynSense (时识科技) — neuromorphic chip company; Lynxi Technologies (灵汐科技)

Key partnerships

Peking University PAICORE Lab (incubation and technology heritage); Collaborating with leading Chinese robotics companies (some projects in active cooperation stage)

Major milestones

Founded May 2025 as Peking University PAICORE Lab spin-off; Completed several hundred million RMB seed round in May 2026; BiGPU architecture development 50% complete; Chip tape-out planned for Q2 2027

Market positioning

First-mover and currently the only native Chinese startup developing a purpose-built robotics 'brain chip' that fuses neuromorphic and GPU compute, positioned as a domestic alternative to Nvidia Jetson for the Chinese embodied intelligence market.

Geographic focus

China (domestic market for robotics brain chips; competing against Nvidia Jetson dominance and other Chinese GPU/neuromorphic chip startups)

Patents and IP

Patent filed for unified ANN-SNN software/hardware method and device (unified instruction format and address encoding for SNN and ANN); 5 patent filings (per Qichacha); 22 trademark registrations

About 殷积磊 (Yin Jilei)

Ex-COO & R&D VP at 知存科技 (Witmem); Chip R&D Director at IBM and GlobalFoundries; Chip R&D roles at MTK (MediaTek) and VIA Technologies; Peking University MS in Microelectronics; 20+ years semiconductor industry experience

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