The DeepSeek V4 technical report shows how a 1 million‑token context forces a redesign of attention, KV‑cache, optimizer, quantization and inference budgeting, turning long‑context capability from a costly showcase into a production‑ready feature for agents, search and Chinese professional tasks.
DeepSeek V4 introduces two flagship models—V4‑Pro with 1.6 T parameters and V4‑Flash with 284 B parameters—offering million‑token context, mixed attention (CSA + HCA), manifold‑constrained residuals, and the Muon optimizer, delivering open‑source performance that rivals top closed‑source LLMs while cutting inference cost dramatically.
DeepSeek released two V4 models—Pro and Flash—both supporting 1‑million‑token context as a standard feature, showcasing top‑tier agentic coding, world‑knowledge, and inference performance, while introducing DSA sparse attention and announcing upcoming large‑scale deployment on Huawei Ascend hardware.
DeepSeek V4 launches in two versions—Pro and Flash—offering 1 M token context, enhanced agent capabilities, world‑knowledge and reasoning performance, a new token‑compression attention mechanism with DSA sparse attention, Huawei compute support, updated APIs, and a migration plan for legacy models.
DeepSeek has launched the open‑source DeepSeek‑V4 series, offering Pro and Flash models with a 1 million token context window, a novel sparse attention mechanism, performance that rivals Opus 4.6 on coding and knowledge benchmarks, tiered pricing, and future cost reductions once Ascend 950 supernodes become widely available.
