DeepSeek V4, Hunyuan Launch Rumored for April

🔑 Enhanced Key Takeaways

• •DeepSeek V4 is led by Liang Wenfeng and features a trillion-parameter Mixture of Experts (MoE) architecture, activating about 37 billion parameters per token for efficient inference[1][2][6].
• •DeepSeek V4 incorporates the Engram memory architecture and supports a 1 million token context window for superior long-term memory and complex interactions[3][5].
• •Tencent's new Hunyuan model has approximately 30 billion parameters, emphasizing long-context processing and Agent task evaluation[1][2].

🛠️ Technical Deep Dive

• •DeepSeek V4 employs a Mixture of Experts (MoE) architecture with a total of 1 trillion parameters, activating approximately 37B parameters per token to maintain manageable inference costs[6].
• •It features native multimodal integration during pre-training, supporting text generation, image understanding/generation, video generation, and cross-modal reasoning[6].
• •Key innovations include the Engram memory architecture for enhanced information retention, a 1 million token context window, and optimizations for domestic Chinese chips like Huawei and Cambricon[3][5][4].
• •DeepSeek V4 builds on a January paper detailing 'conditional memory' mechanisms, with collaborations like Baidu for AI search capabilities[3].

🔮 Future ImplicationsAI analysis grounded in cited sources

⏳ Timeline