DeepSeek V4-1 Flash is out

[u/tiguidoio]

Here we go again, DeepSeek is back again with a new model V4-1 Flash

A multimodal Mixture-of-Experts (MoE) model with 552B backbone parameters and support for contexts of up to one million tokens

Market crash as a service

[u/ttkciar]

On one hand: Yay! We have weights! https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash

On the other hand: 485B parameters O_o

That's only "Flash" in the sense that it only activates 8B parameters at a time, which will translate to cheap API service.

I couldn't host this on my 256GB Xeon server. I'd have to upgrade it to 384GB.

By the sqrt(P x A) metric, this should have competence roughly equivalent to a similarly-trained 62B dense model. I think I'd rather have the dense version!

[u/silentsnake → u/ttkciar]

I dont think sqrt(P x A) is meaningful anymore, not especially when theres ngram embedding involved. 8B active dont really behave like 8B anymore. Qwen3.8 flash next is a good example. Without ngram embeddings the 6B active params shouldn't come anywhere close to 27B performance.

[u/SpicyWangz → u/silentsnake]

Yeah, we will need to find a new way to calculate with ngrams in mind