Hong Kong launches DeepSeek-based HKGAI-V3 optimized for domestic chips

The Hong Kong Generative AI Research and Development Centre (HKGAI) launched HKGAI-V3, a new large language model built on DeepSeek V4 and optimized specifically to run on domestic chips rather than NVIDIA hardware. The headline efficiency claims are striking: over tenfold token compression and an almost hundredfold increase in uninterrupted agent runtime, with an HKGAI-V3-based agent platform reportedly operating stably for up to 28 hours continuously.

The domestic-chip optimization is the strategic core. Amid US export controls limiting access to advanced NVIDIA accelerators, building frontier-class models that run efficiently on Chinese-made silicon is a sovereignty and resilience play. The claimed token-compression and long-runtime figures, if validated, would address two of the most practical barriers to deploying autonomous agents at scale — cost (fewer tokens) and reliability over long-horizon tasks (28-hour uninterrupted runtime).

DeepSeek itself is reportedly nearing a deal to raise $7.4 billion for its open-source AI efforts, underscoring the commercial momentum behind the DeepSeek lineage that HKGAI-V3 builds upon. DeepSeek remains a reference point for cost-efficient, open frontier models, and is one of the named options inside Microsoft's Azure AI Foundry.

The efficiency claims warrant skepticism until independently benchmarked — tenfold compression and hundredfold runtime gains are extraordinary figures that need scrutiny on what tasks and at what quality cost. Still, the broader signal is real: Chinese and Hong Kong labs are aggressively pursuing the domestic-hardware AI stack. The DeepSeek community remains passionate, with an r/DeepSeek thread on geopolitical pressures drawing heated engagement. Watch for third-party validation of the runtime and compression claims.