DeepSeek v4 Flash MTP is a training optimization. It doesn't make inference run faster, it must run the entire model forward as the "verifier." This is in the paper, and this is why the docs they release do not mention using it for accelerated inference.

Eventually, I'm going to stop writing stuff like this @dang, because even though it is literally being read by a human, it's going to just be copy and pasted into a chatbot, which will actually spend the time trying to comprehend what I am saying.

> MTP in Inference. Our MTP strategy mainly aims to improve the performance of the main model, so during inference, we can directly discard the MTP modules and the main model can function independently and normally. *Additionally, we can also repurpose these MTP modules for speculative decoding to further improve the generation latency.*[1]

(emphasis mine)

> Instead of predicting just the next single token, DeepSeek-V3 predicts the next 2 tokens through the MTP technique. Combined with the framework of speculative decoding (Leviathan et al., 2023; Xia et al., 2023), it can significantly accelerate the decoding speed of the model.[2]

> As DeepSeek-V3, DeepSeek-V4 series also set MTP modules and objectives. Given that the MTP strategy has been validated in DeepSeek-V3, we adopt the same strategy for DeepSeek-V4 series without modification.[3]

[1]: https://arxiv.org/pdf/2412.19437#subsection.2.2

[2]: https://arxiv.org/pdf/2412.19437#subsubsection.5.4.3

[3]: https://arxiv.org/pdf/2606.19348v1#subsection.2.1

Side comment: I feel you may be too cynical towards your fellow commenters.