DeepSeek-V4 preview drops with 1.6T parameters, 1M context

// 45d agoMODEL RELEASE

DeepSeek-V4 preview drops with 1.6T parameters, 1M context

DeepSeek has officially launched the preview of DeepSeek-V4, a flagship Mixture-of-Experts (MoE) model series featuring up to 1.6 trillion parameters and a native 1-million-token context window. This open-weights release includes the massive V4-Pro and a more efficient V4-Flash variant, both optimized for advanced coding, native multimodality, and high-performance agentic reasoning.

// ANALYSIS

DeepSeek-V4 is a strategic strike against the high inference costs of Western frontier models, offering GPT-5 level reasoning at an order of magnitude lower price point.

–The 1.6T parameter MoE architecture is highly efficient, activating only 37-49B parameters per token to enable low-latency inference on high-end consumer hardware.
–Native multimodality (text, image, video, audio) trained from scratch indicates DeepSeek is no longer just "catching up" but setting the pace for integrated foundation models.
–"Engram Memory" and "mHC" architectures solve the long-context degradation problem, making it a premier choice for repository-level coding tasks.
–By maintaining an aggressive Apache 2.0 open-weights stance, DeepSeek is effectively commoditizing high-end intelligence and forcing a pricing war.
–Optimization for "Thinking Mode" with adjustable reasoning effort makes it the most flexible backbone for autonomous AI agents currently on the market.

// TAGS

deepseekdeepseek-v4llmopen-weightsmoereasoningai-codingagentmultimodal

DISCOVERED

45d ago

2026-04-24

PUBLISHED

45d ago

2026-04-24

RELEVANCE

10/ 10

AUTHOR

Lopsided_Dot_4557

// KEEP READING

More AI developer news from the feed

EXPLORE FULL FEED

OPEN SOURCE51m ago

Agent-Reach is an open-source Python tool that equips AI coding agents with zero-config, API-free search and scraping capabilities across platforms like Twitter, Reddit, YouTube, and XiaoHongShu.

Agent-Reach is an open-source Python toolkit designed to give AI agents (like Claude Code, Cursor, and Windsurf) direct web search and scraping abilities without the need for expensive API fees or complex setups. By serving as an installer and routing scaffold, it configures locally managed CLI tools (such as yt-dlp and platform-specific scrapers) so that agents can fetch real-time web content, social media posts, and video transcripts directly. The system emphasizes privacy by keeping credentials and cookies local, and handles smart routing to call the most appropriate tool for a given platform.

OPEN SOURCE51m ago

Personal AI Infrastructure is an open-source framework by Daniel Miessler that acts as a modular "Life Operating System" to scaffold and coordinate personal AI assistants.

Personal AI Infrastructure (PAI) is a comprehensive scaffolding framework that integrates AI tools, context, and personal preferences into a unified platform. It leverages core components like TELOS (for articulating values and goals), Pulse (a local dashboard for monitoring state and work), Skills (functional capabilities), and Memory (contextual history) to create a highly personalized, local AI agent that adapts and improves its assistance over time.

VIDEO1h ago

AI video models fail stunt benchmark

X user YourAlphaMom tested leading AI video models—Kling 3.0, Gemini Omni Flash, Grok Imagine 1.5, and Seedance 2.0—with a complex stunt sequence requiring a bridge jump and car takeover. None of the models successfully generated the required physics, transitions, and continuity, highlighting the limitations of current generative video technology.