DeepSeek V4 Multimodal Model Imminent, Prioritizing Huawei Chips

DeepSeek V4 Multimodal Model Imminent, Prioritizing Huawei Chips

Overview

Chinese AI company DeepSeek is about to launch V4, its first multimodal large language model supporting text, image, and video generation. The release coincides strategically with China's "Two Sessions" political meetings.

Domestic Chip-First Strategy

V4's most significant strategic move is prioritizing optimization for domestic chips — Huawei and Cambricon — over Nvidia and AMD. This represents a crucial step toward building a non-NVIDIA AI tech stack and reducing dependency on American semiconductors, aligning with the broader US-China tech competition.

DeepSeek's Rise

Last year, DeepSeek R1 shook the AI world by challenging OpenAI with minimal compute resources. V4 marks its first major product launch in over a year, representing a significant leap from text-only to multimodal capability. However, Anthropic's accusation of "industrial-scale" capability extraction has cast a shadow over the release.

Looking Ahead

V4 will test whether domestic AI chips can support world-class model training and inference. Success would provide critical validation for China's AI independence ambitions and accelerate diversification of the global AI chip supply chain.

In-Depth Analysis and Industry Outlook

From a broader perspective, this development reflects the accelerating trend of AI technology transitioning from laboratories to industrial applications. Industry analysts widely agree that 2026 will be a pivotal year for AI commercialization. On the technical front, large model inference efficiency continues to improve while deployment costs decline, enabling more SMEs to access advanced AI capabilities. On the market front, enterprise expectations for AI investment returns are shifting from long-term strategic value to short-term quantifiable gains.

However, the rapid proliferation of AI also brings new challenges: increasing complexity of data privacy protection, growing demands for AI decision transparency, and difficulties in cross-border AI governance coordination. Regulatory authorities across multiple countries are closely monitoring these developments, attempting to balance innovation promotion with risk prevention. For investors, identifying AI companies with truly sustainable competitive advantages has become increasingly critical as the market transitions from hype to value validation.

From a supply chain perspective, the upstream infrastructure layer is experiencing consolidation and restructuring, with leading companies expanding competitive barriers through vertical integration. The midstream platform layer sees a flourishing open-source ecosystem that lowers barriers to AI application development. The downstream application layer shows accelerating AI penetration across traditional industries including finance, healthcare, education, and manufacturing.