Serving DeepSeek-V4: why million-token context is an inference systems problem
Together AI has detailed the architectural innovations behind DeepSeek-V4's ability to handle a 1 million token context window. The model employs a hybrid attention design that compresses context before storing it in the KV cache, significantly reducing memory pressure. This architectural shift transforms the challenge of long-context inference from a model capability into an inference systems problem, requiring optimized serving engines to manage cache layouts and batching effectively. AI
IMPACT DeepSeek-V4's architectural innovations enable practical long-context inference, pushing the boundaries of what's possible for AI applications requiring extensive context.
