OPEN_SOURCE ↗
YT · YOUTUBE// 3h agoMODEL RELEASE
DeepSeek V4 drops 1.6T open weights, 1M context
DeepSeek releases a 1.6 trillion parameter Mixture-of-Experts model featuring a 1 million token context window and MIT-licensed open weights. Optimized for Huawei Ascend NPUs, it targets SOTA agentic coding and complex reasoning benchmarks at a fraction of competitors' costs.
// ANALYSIS
DeepSeek V4 is a watershed moment for open AI, delivering frontier-level reasoning and massive context efficiency without Nvidia silicon.
- –Hybrid Attention architecture reduces KV cache by 90% to enable efficient 1M token processing.
- –The 1.6T Pro model rivals closed-source giants like GPT-5 in agentic coding and STEM reasoning.
- –Native optimization for Huawei Ascend 950PR proves high-performance LLM training is possible outside the CUDA ecosystem.
- –Aggressive API pricing ($1.74/1M input tokens) undercuts the market by orders of magnitude for its performance class.
- –Engram Memory architecture enables repository-level code analysis, making it a primary choice for autonomous dev tools.
// TAGS
deepseek-v4llmopen-weightsai-codingagentinferencereasoning
DISCOVERED
3h ago
2026-04-24
PUBLISHED
3h ago
2026-04-24
RELEVANCE
10/ 10
AUTHOR
Prompt Engineering