If you're serving million-token-context workloads, this breaks down the real bottlenecks — compressed KV cache layouts, prefix caching, and kernel maturity on HGX B200 — so you can pick endpoint profiles and reason about long-context inference cost/latency instead of treating context length as a free model feature.
DeepSeek-V4 makes million-token context a serving-systems problem.
Transcript
DeepSeek-V4 makes million-token context a serving-systems problem. Together AI explores the inference work behind V4 on NVIDIA HGX B200, including compressed KV layouts, prefix caching, kernel maturity, and endpoint profiles for long-context workloads.
