YHK - yet another hacker news clone

Seriously, if a single politician stepped forward and said "i'll bring down ram prices" they could then shoot a puppy and call me a slur and I'd still go out and doorknock for them.

Memory companies have price fixed multiple times. They've paid hundreds of millions in fines. wikipedia even has a page on it. https://en.wikipedia.org/wiki/DRAM_industry_price_fixing.

Look at the financials of these companies, they're all making obscene margins and do they plan to increase production? No. Micron is doing a stock buy back to pump the price of their share.

The Micron CEO just recently said this is the exact plan https://www.theregister.com/systems/2026/10/01/ram-supply-se...

There's sanctions, tarrifs, and a DOJ who doesn't give a shit. Until we can fix that the insanity will continue. Phones will be unaffordable. Laptops will be obscene. Gaming consoles will be thousands of dollars. Desktops will be dead.

If you're waiting for some David Ricardo equation to happen, tough cookies, it's not coming.

The market is legally locked down and we're in hostage pricing mode.

And what's the story? You can't afford electronics because we're using it to build robots to take your job? I mean ...

Nobody is coming to save us. That's our job.

I think, considering the size of this model, it's closer to a Pro than a Flash on everything other than speed

He doesn't ruin the cost of memory. Advances in memory size and speed are now in full speed mode. Expect drastic increase in the upcoming years. Big factories are in the making and planned. Gigalab in the US and many others in the east. Since 2010 we have computers with 16gb as being normal. Finally we are moving into a new era where the standard will be 64gb next year and 128 in 2028. Hopefully we reach 1tb in 2030.

one can make a fine gaming pc for ~$350

1660 ti, 4790k, 16gb ddr3

There's no BF16, original full quality weights are quantized already and 510GB.

Then good portion of those weights are n-grams (~200GB) that don't need to be in VRAM.

Then KV cache of that model is super lightweight at ~1GB per 1M tokens. If HBF succeeds, then accelerator with 16GB of VRAM and 1TB HBF/NAND is probably all you need (?).

What are you talking about? The model is native NVFP4, why you run it at any precision higher than that?

I just un-retire my pair of 1080Ti for some small models development because the current GPU prices literally make me sad.

The bulk of its weights are natively MXFP4. And engram values don't need to be in vram.

Not quite: not all of this needs to be in VRAM

It has a set of n-gram tables which you can stream from system RAM or even NVMe

That said it’s still quite big! I can’t fit it on my DGX Spark, though I believe you can if you have two?

It's dangerous to go alone. Take this: [1]

I reimplemented most of the features of the Deepseek v4.1 flash paper (apart from quantization aware training which doesn't make sense because my implementation uses float32 precision anyways)

I'm currently learning how to distill reasoning traces (check my other github repositories) but I think that a locally selfhostable deepseek is possible with my mixture of experts sharding mechanism. I decided to optimize everything for CPU parallelization, with the idea that the KV cache and meta model have to run from CPU RAM anyways, so the experts can also be loaded/unloaded at runtime if needbe, to save more RAM.

Anyways, would love to see someone train this on their own datasets. Currently my pipeline is kinda optimized for parquet and zim files.

[1] https://github.com/cookiengineer/gonano

> Even so why would anyone not sleep on a model they cannot run?

Because it's an open model so providers compete on price.

The article isn't just about running locally though. The author is saying it's super cheap to run the model through Opencode Go (and presumably OpenRouter etc.) Personally I'm always most excited by models I can actually run locally, but even these huge open source models open up the competitive landscape for companies to let you call models via an API or just lease compute. And they don't have to charge you to offset research, training, huge staffs of the best minds in the world, crazy PR etc. I think that's a big win for customers and buts competitive pressure on the frontier labs as well.

You can run it locally for the price of a decent car, or run it on somebody else's hardware at vast.ai or a similar provider for much less. What's not to like?

No, you won't get frontier-level intelligence on a 1070Ti. Yes, it should be illegal to do what Altman did. Since we clearly don't live in the best of all possible worlds, we need to settle, and DS4.1 Flash is a good place to do that. For tasks that don't require vision to support, I personally like the NVFP4 quant of GLM 5.3 from Local Inference Lab better, but they are both well beyond awesome.

Don't think so.

Nah fam, not true, also DS edges it out on coding / dev tasks.

Opencode Go gives only 6300 requests for glm and 23 000 for deepseek. And, if I wanted to, I would be able to do all my work on $10 plan with deepseek. It’s very cheap.

they should be freaking out because every time the chinese labs or non "frontier" labs release a model that is only a few months behind and much cheaper than the openai/anthropic models it shows that they don't deserve their valuations

It would look like major chaos in the markets.

People tend to conflate the question "is AI a useful technology?" with "are the AI companies going to do well?" but they're surprisingly separated in practice, with either one able to be true while the other is false. There is a lot of money tied up in a lot of hardware with a lot of loans made against that hardware as collateral all based on the assumption that AIs are going to need more and more and more and more hardware and whoever has the hardware wins. If a much better model comes out that requires vastly less hardware, or even more accurately, merely charges vastly less than the current AI companies, then to a first approximation (barring Jevon's paradox, and bearing in mind there's no timeline guarantee on that) all that hardware becomes much less valuable for being grotesquely oversupplied relative to what is necessary, and even though that would generally make AI objectively more useful than it was before, it would cause mass financial chaos in the markets.

The markets need a very particular rate of progress. It isn't entirely clear to me that it's even a possible rate of progress, it may be overconstrained, but they certainly don't have plans for the AI models to get commoditized on the timeframes of these vast, vast array of loans being made against hardware as collateral. Spend a metric shit ton of money to kill all your competition then charge monopoly rent on the one thing absolutely everyone needs doesn't work if you can't economically "kill all your competition" because the economics favor them in the spending spree.

And then, based on the fact that this is not even remotely complicated logic, there are plenty of people who are fully aware that they have a lot of money tied up in not running around telling everyone how wonderful the cheap models have become.

Do you mean Fable 5.1? Or Opus 5.5? I'm not sure what you're working on but for me DS 4.1 flash isn't nearly at their level. For the price it's obvious very impressive, though Luna 6.0 is excellent too.

I think it also has a bit to do with the AI sector of tech still moving at lightning speed.

Theres already models that outdo DS 4.1 flash in cost/performance. Luna 6 on max effort for example. Luna also doesn't care what time of the day it is for cost calculation.

And I'm sure by the time people ask why Luna 6 is being slept on there will be another cost/performance king

If DS4.1 impresses you I would be really interested to see your comparison to GLM 5.3. I switched from the one to the other and even if GLM 5.3 is a bit slower I don't think I'll be going back.

What inference provider are you using?

You can ask them directly, Daniel Han-Chen is pretty responsive.

Since they adhere to the same API spec, you can hook any model. It takes one line edit in /etc/hosts

There are some quirks if your harness use unsupported features of course.

Have you compared it against actual SOTA models like latest Fable or Astra?

Technically yes, but has been reported to be quite benchmaxxed. In practice Deepseek Flash 4.1 and GLM 5.3 might therefore still outperform Mimo 2.6 pro.

> Obviously can’t use it at work

I do wonder how long it'll be before a us-hosted offering is available via bedrock, copilot, etc.

You are running this now? :o

Your comment seems to imply there's a good guy in a this. I just see the inevitable end of an era, championed by predictably selfish actors.