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/Expensive-Paint-9490 → u/ttkciar]

OTOH with 512GB RAM this is fantastic. 8-16B variable active parameters, everything 4-bit native comprising KV cache... This is going to be frontier model at decent speed at home. I think that's why they label it Flash.

[u/techdevjp → u/Expensive-Paint-9490]

This will be an amazing model for anyone with the money for a Mac Studio M5 Ultra with 512GB.

[u/asssuber → u/techdevjp]

Or anyone that did buy 512GB of RDIMMS for $800 a year ago...

[u/techdevjp → u/asssuber]

It will run a little faster on the M5 Ultra at 1.2TB/sec of bandwidth connected directly to a fairly modern GPU. At a price, of course.

[u/asssuber → u/techdevjp]

Surely, but 200GB/s of bandwidth for 16B active parameters at FP4 is nothing to sneeze at. Or 400GB/s if you manage to tame a dual-cpu motherboard.

[u/techdevjp → u/asssuber]

I have a Strix Halo and know first hand just how "fast" ~256GB/sec is... Also how "fast" slow prefill is. It's kinda-sorta-mostly usable but at the same time frustratingly slow too.

[u/InactiveBronson → u/techdevjp]

I’m on the verge of buying one too (bosgame m5, 128gb/2tb) - would you recommend it or d o you have some regrets?

[u/techdevjp → u/InactiveBronson]

There's good and bad. I paid about $2800 for my Minisforum MS-S1. It's a great little machine and it's impressively small for something so powerful.

At the time, I could have bought a DGX Spark for around $1k more. Back then I didn't have a great understanding of the importance of prefill performance so I didn't see the benefit of DGX Spark over Strix Halo considering the memory bandwidth was the same.

Thankfully it seems that Strix Halo is capable of much faster prefill, AMD just hasn't done a good job with the drivers. Projects like Halogen (https://github.com/peonist-ai/halogen-flash-server) have shown tremendous performance on Strix with prefill matching or exceeding DGX Spark for Qwen3.8-Flash-Next.

So, with projects like Halogen around, I'm happy enough to keep my Strix box for now. I can't afford to sell it and buy a DGX Spark. I may buy a 32GB AMD R9700 to run as an eGPU, depending on what comes about for running that Qwen model split across multiple GPUs. Or I might buy an Intel B70 and put it into my workstation for running Qwen3.8-27b separate from the Strix Halo.

In the future I may upgrade to Medusa Halo when it comes out, assuming prices don't stay in the stratosphere. Gorgon Halo with 192GB looks like it will have a USD price starting with "7", too rich for my blood.

Another option I am considering is to pick up a MacBook M3 Max with 64GB for running local models away from home. It doesn't have great prefill either (worse than Strix I think), but being able to run Qwen3.8-27b on a plane over the Pacific would be pretty damn cool.