DeepSeek is set to disrupt the AI landscape once again with the anticipated release of DeepSeek V4, rumored for launch around mid-February 2026, coinciding with the Spring Festival. This next-generation model is expected to feature a revolutionary architecture called Engram, which separates reasoning from static memory, potentially outperforming industry giants like OpenAI and Anthropic in coding and long-context tasks.
DeepSeek V4: Key Release Information
DeepSeek V4 marks a major architectural shift from its predecessors, moving away from brute-force scaling toward a more efficient, “thinking-first” approach.
-
Release Date: Expected mid-February 2026 (Spring Festival).
-
Primary Variants:
-
V4 Flagship: Optimized for heavy, long-form coding and complex technical projects.
-
V4 Lite: Focused on speed, responsiveness, and cost-effective daily interaction.
-
-
Performance: Internal benchmarks suggest that V4 could surpass Claude 3.5 and GPT-4o in specific coding dimensions, multi-file reasoning, and structural coherence.
The Engram Architecture: A Game Changer
The most significant innovation in DeepSeek V4 is the Engram architecture. This shift addresses the “memory vs. reasoning” tension found in traditional Mixture-of-Experts (MoE) models.
-
Memory Separation: Instead of forcing the model to store factual knowledge in reasoning layers, Engram offloads static memory to a scalable lookup system.
-
Hardware Efficiency: Engram can store massive knowledge tables (billions of parameters) in CPU RAM rather than expensive GPU VRAM, drastically reducing deployment costs.
-
Logical Prowess: By offloading memory, the GPU is free to focus entirely on computation, planning, and code structure.
Benchmarks and Coding Superiority
DeepSeek has already published research on the Engram architecture, showing impressive results against standard models.
-
Long-Context Stability: V4 is expected to maintain coherence over significantly longer prompts compared to current industry standards.
-
Multi-File Reasoning: The model is specifically designed for complex software engineering tasks, such as refactoring large codebases and managing project-wide logic.
-
RULER Benchmarks: Research shows that Engram-based models excel in multi-hop reasoning and symbolic tasks, outperforming 27B-parameter baselines while using less training compute.
DeepSeek’s Strategic Pattern
The launch of V4 follows a highly deliberate release cycle. DeepSeek V3 (December 2024) established the company's efficiency credentials, while DeepSeek R1 (January 2025) introduced specialized reasoning capabilities. V4 is viewed as the convergence of these two paths—integrating R1’s “long chain of thought” directly into a high-performance general model.
Impact on the Global AI Race
DeepSeek’s commitment to open-source development continues to put pressure on Western “closed-source” developers like OpenAI and Google.
-
Lower Inference Costs: By utilizing CPU RAM for memory retrieval, DeepSeek V4 could offer top-tier performance at a fraction of the token cost of its competitors.
-
Democratizing High-Level Coding: An open, cost-efficient model that beats GPT-4 in coding would allow developers worldwide to build enterprise-grade software with minimal overhead.
As the AI community waits for the official mid-February drop, the technical consensus is clear: DeepSeek V4 isn't just a bigger version of what came before; it’s a fundamental rethinking of how AI models should process and store information.
