May 19, 2026 · Artificial Intelligence

How New LLM Architectures Like Gemma 4 and DeepSeek V4 Cut Long‑Context Costs

Recent open‑weight LLMs such as Gemma 4, Laguna XS.2, ZAYA1‑8B, and DeepSeek V4 introduce KV‑cache sharing, per‑layer embeddings, layer‑wise attention budgeting, and compressed attention mechanisms that dramatically reduce memory and compute overhead for very long contexts while preserving model quality.

Efficient InferenceKV sharingLLM

0 likes · 25 min read

How New LLM Architectures Like Gemma 4 and DeepSeek V4 Cut Long‑Context Costs

ArcThink

Apr 25, 2026 · Artificial Intelligence

DeepSeek V4’s Silent Launch: 1.6 T Parameters, Triple Innovation, and Redefined Accessibility

DeepSeek V4 quietly debuted with a 1.6‑trillion‑parameter MoE model, introducing CSA+HCA compressed attention, mHC manifold‑constrained hyperconnections, and the Muon optimizer, achieving 1M‑token context at a quarter of V3’s cost, top Codeforces and LiveCodeBench scores, a 1/7 Opus price, MIT open‑source licensing, and dual‑stack Ascend NPU/NVIDIA GPU support.

DeepSeek V4Large Language ModelManifold-constrained Hyperconnection

0 likes · 17 min read

DeepSeek V4’s Silent Launch: 1.6 T Parameters, Triple Innovation, and Redefined Accessibility

How New LLM Architectures Like Gemma 4 and DeepSeek V4 Cut Long‑Context Costs

DeepSeek V4’s Silent Launch: 1.6 T Parameters, Triple Innovation, and Redefined Accessibility

How New LLM Architectures Like Gemma 4 and DeepSeek V4 Cut Long‑Context Costs

DeepSeek V4’s Silent Launch: 1.6 T Parameters, Triple Innovation, and Redefined Accessibility