Event Background

DeepSeek V4 achieves 1.6T parameters with only 27% of the compute cost of prior models, reduces KV cache by 90%, and offers API pricing at 1 RMB per million tokens. Its open-source nature and full-stack compatibility with Chinese chips are disrupting enterprise AI procurement.

Key Points

  • V4-Pro’s cost for 1M-token inference is 1/4 of GPT-4 Turbo
  • Fully optimized for Huawei Ascend 910B/950, enabling国产算力 independence
  • Real-world tests show code generation and agent performance matching Claude Sonnet 4.6
  • Hallucination rates and tool-call reliability still require external HARNESS layers

Hongshugu's View

DeepSeek V4 isn’t a technical breakthrough—it’s a cost paradigm shift. Enterprises must stop selecting models by leaderboard rankings. The only scalable path is open-source base + controllable scaffolding. System architecture matters more than model size.

Enterprises must act now: First, form an AI Systems Engineering team to assess V4 integration cost in internal workflows. Second, procure HARNESS framework development services, not just API access. Third, co-build validation labs with domestic chip vendors like Huawei Ascend and Cambricon. Replace point purchases with system design.

Hongshugu is designing V4-based agent middleware for manufacturing giants in the Greater Bay Area and launching an open-source AI base innovation challenge to accelerate industrial adoption.