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HCA

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Jul 14, 2026 · Artificial Intelligence

How DeepSeek V4’s CSA+HCA Architecture Turns Million‑Token Context into a Cheap Feature

DeepSeek V4 introduces a hybrid CSA/HCA attention mechanism and a Mixture‑of‑Experts design that reduces inference cost to 27% of its predecessor, enables a 1‑million‑token context as a standard feature, and runs efficiently on both NVIDIA GPUs and Huawei Ascend NPU, dramatically lowering the barrier for Java developers to integrate large‑scale AI.

CSADeepSeek V4HCA

0 likes · 10 min read

How DeepSeek V4’s CSA+HCA Architecture Turns Million‑Token Context into a Cheap Feature

Lao Guo's Learning Space

Apr 30, 2026 · Artificial Intelligence

How DeepSeek V4’s CSA + HCA Break the Million‑Token Barrier

Traditional full‑attention cannot handle million‑token contexts due to exponential compute and memory growth, but DeepSeek V4’s Compressed Sparse Attention (CSA) and Heavily Compressed Attention (HCA) compress, sparsely index, and precisely compute tokens, cutting KV cache to 10% and FLOPs to 27% while enabling a 1‑M token window on a single GPU.

Attention MechanismCSAHCA

0 likes · 12 min read

How DeepSeek V4’s CSA + HCA Break the Million‑Token Barrier

DeepHub IMBA

Apr 27, 2026 · Artificial Intelligence

DeepSeek‑V4 Deep Dive: Engineering Million‑Token Context Efficiency

The article provides a thorough technical analysis of DeepSeek‑V4, detailing how mixed sparse attention (CSA + HCA), manifold‑constrained hyper‑connections, the Muon optimizer, FP4 quantization, and a suite of infrastructure tricks enable stable training and inference with up to one‑million token contexts while achieving state‑of‑the‑art benchmark results.

CSADeepSeek V4FP4 quantization

0 likes · 22 min read

DeepSeek‑V4 Deep Dive: Engineering Million‑Token Context Efficiency