DeepSeek-V4-Flash Official Version Open-Sourced
DeepSeek-V4-Flash Official Version is now open-sourced with post-training breakthroughs, 304B parameters, and efficient GGUF quantization for affordable local deployment.
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DeepSeek-V4-Flash Official Version Released and Open-Sourced Simultaneously
While retaining the same model architecture and parameter scale as DeepSeek-V4-Flash-Preview, they re-did post-training (specialized training for specific tasks to teach the model how to answer questions, how to call tools, and how to complete tasks according to requirements). It has surpassed the V4-Pro preview version from three months ago on multiple benchmarks.
At a time when everyone is competing on parameter counts (trillion-parameter models have become the norm), DeepSeek once again chose a clever direction (post-training) and proved it works.
On Artificial Analysis’s large model intelligence index vs. single-task cost comparison chart, the horizontal axis is the cost of completing one task—the further left, the cheaper; the vertical axis is model intelligence score—the higher up, the stronger the capability.
Therefore, an ideal model should stay as close as possible to the upper-left corner: both cheap and smart. The position of DeepSeek-V4-Flash-0731 (Max), along those two dashed lines, has been called by netizens the “DeepSeek kill line.”
What I care about most is still local deployment. For enterprise applications, local models are almost a must.
