DeepSeek v4 PRO running in DwarfStar on a DGX Station.
Can go faster, already peaks 50 t/s without DSpark: dynamic VRAM/RAM allocation of experts based on past statistics, 4k t/s prefill on big chunks. VRAM/RAM layer-major streaming. Mixed RAM/VRAM inference requires care.
Deepseek just gave away the thing everyone else charges $200 a month for.
Your feed calls it an open source coding agent. It is not. They open sourced the harness. The harness is everything around the model: which tools it gets, what loop it runs in, what enters context, what
Autonomous agents fail when prompts get too short (Brevity Bias) or when iterative memory rewrites wipe out accumulated experience (Context Collapse).
Stanford and SambaNova published Agentic Context Engineering (ACE, ICLR 2026) to solve this without updating model weights.
API: Developers get the same access
For developers, also makes DeepSeek-V4-Flash available through its API. The basic setup is: → Enter the API Management panel → Select Official mode → Choose Full Access → Create an API Key → Copy the
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