DeepSeek V4 Preview and the 1M-context open model race
DeepSeek's V4 Preview is another signal that Chinese AI labs are competing hard on context length, active parameters, and cost.
Source
Why I saved it
DeepSeek is important to track because it changed how many developers think about open models and cost-performance.
The V4 Preview release keeps that pattern going: large context, open-source positioning, and separate Pro and Flash variants.
My notes
- DeepSeek-V4 Preview is presented around cost-effective 1M context.
- DeepSeek-V4-Pro is listed as 1.6T total parameters with 49B active.
- DeepSeek-V4-Flash is listed as 284B total parameters with 13B active.
- The API supports developer workflows through familiar interfaces.
What I want to remember
Long context is becoming normal, but long context alone is not enough. I still want to see retrieval quality, tool use, latency, cost, and how stable the model is over a full agent loop.