DeepSeek-V4: Open Source at the Frontier

AI Study Group · Intermediate ·🧠 Large Language Models ·2mo ago

About this lesson

DeepSeek just released V4 — a 1.6 trillion parameter open source model with a 1 million token context window. In this video, we break down everything: the hybrid CSA+HCA attention system, Manifold-Constrained Hyper-Connections (mHC), the Muon optimizer, benchmark results vs GPT-5.4, Gemini-3.1-Pro, Claude Opus 4.6, and what it actually takes to run it locally. #AI #ai #aitrends #aitechnology #techtrends #deepseek #deepseekv4 #openmodel * This video was produced with the assistance of AI tools and may contain errors.

Original Description

DeepSeek just released V4 — a 1.6 trillion parameter open source model with a 1 million token context window. In this video, we break down everything: the hybrid CSA+HCA attention system, Manifold-Constrained Hyper-Connections (mHC), the Muon optimizer, benchmark results vs GPT-5.4, Gemini-3.1-Pro, Claude Opus 4.6, and what it actually takes to run it locally. #AI #ai #aitrends #aitechnology #techtrends #deepseek #deepseekv4 #openmodel * This video was produced with the assistance of AI tools and may contain errors.
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related Reads

📰
Building Your First Model Context Protocol (MCP) Server with TypeScript and Zod
Learn to build a Model Context Protocol (MCP) server with TypeScript and Zod to integrate Large Language Models with external environments
Dev.to AI
 📰
Beyond Code Generation: How OmniSVG Rethinks Vector Graphics with Vision-Language Models
Learn how OmniSVG uses vision-language models to rethink vector graphics beyond code generation
Dev.to · Shrijith Venkatramana
 📰
LangGraph Checkpointing: Three Production Rewrites to Stop Losing State
Learn how to implement LangGraph checkpointing to prevent state loss in production environments
Dev.to · Elena Revicheva
 📰
AI builder essentials: tokens, context windows and RAG 101
Learn the essentials of AI building with tokens, context windows, and RAG 101 to improve your LLM interactions
Dev.to · Tilde A. Thurium
Up next
5 Levels of AI Agents - From Simple LLM Calls to Multi-Agent Systems
Dave Ebbelaar (LLM Eng)
Watch →