bertili

DeepSeek is truly making a difference on many levels, but the one most refreshing is how they just deliver once again with no fanfare or drama. Not even a website. Just hand us over the goods for free the DeepSeek way.

Thats a feature, not a bug :)

Not clear if it can run iOS apps at all?

This would presume we knew what consciousness and pain is. We don't. We we are clueless. There is not even a starting point of a science here.

In this light your viewpoint is dogmatic. LLMs may help to offer a new perspective on consciousness and we should at least be open to that until some better theories arise.

Not apparent at first, but this is a TypeScript to c++ compiler at the core (https://github.com/geastack/compiler), with bindings for various platforms.

They mixed up DeepSeek 4.1 Flash with something else on this page, possibly DeepSeek 4.1 Flash means Gemini 3.8 Flash.

The evolutionary way: Something that is very good at copying itself, will copy itself and gobble up resources, which are finite. Humans took the natural resources from animals and infinite scrolling took the mind-resources from kids. Now animals and our children are fewer and have difficulties to reproduce.

The bigger story is the compute efficiency - its been running at 300t/s the last days.

DeepSWE scores 75.4 - that's the best score so far. And it's crazy cheap! Google held the top a few hours today with Gemini 3.8 Flash, but now second to Spark 1.3. All this competition will drive prices down!

A fifth of the cost of Opus 5! Google is certainly pushing the completion with this.

0 days later: Qwen 3.8 Flash Next: Let's cut GLM 5.3 Flash parmeters in half and active parameters to a third!

Chinese models had 94% reduction in parameters (from 2.8T/104B to 180B/6B) in 6 weeks, while staying close to the same quality.

The point is open AI. "Open" as in open weights, open research, open future.

This is going so fast! What a time to be on hackernews:

July 16th: The "Kimi K3 moment" - China has caught up to Opus!

4 weeks later: GLM 5.3 - Same performance, but cut the amount of parameters and cost to a third!

12 days later: GLM 5.3 Flash - Almost GLM5.3 performance but cut the parameters in half, cut prices to a fifth and serving on Chinese chips!

I can't shake this the existential feeling that this compact series of 27G bytes represent something profound and universal.

And more context:

Same score as the latest DeepSeek Flash 0731 which has 284B parameters! (13B active)

Its also the second best Qwen model, much better than Qwen 3.7 Max, but significantly below Qwen 3.8 Max.

Wow. Speed improved as well. 200t/s on a RTX 5090!

https://x.com/sgl_project/status/2088281320422322413

This will be roughly on pair with Kimi K3, but using a third of its parameters.

Just 4 weeks ago the "Kimi K3 moment" was seen as a threat to Closed AI and in less than a month Z.ai have cut the parameter/RAM barrier to a third.

Congratulation to Z.ai and all the hard working Chinese researchers who are quitely boiling the frog.

Musk: Open Chinese models will rival Fable 5 in Q1 2027

JieTang (Founder of Z.ai): It won't take that long

https://x.com/i/trending/2067626647050670400?lang=en

DwarfStar (https://github.com/antirez/ds4) supports GLM 5.2 and DeepSeek. Not only for toying, but for getting work done.

The 27B have many more active parameters than much bigger models such as DS4Flash, MiniMax etc, which makes it punch above its tiny weight. A great fit for a 5090 in a closet for meat-and-potatoes, kind of work.

That looks promising! As models become a commodity, this may turn out to be the real AI gold rush.

Is there any (near future) technology that would permit burning this terrabyte into some kind of ROM chip?

Wait.. the Qwen Max models have never been open-weight. But it sure sound like that's what they intend now?

"Qwen3.8 is launching and going open-weight soon! With a massive 2.4T parameters..."

AGI is almost here, but first, one more thing... a keyboard controller!

Legislators, please require 10 seconds of load screen with a picture of a tree, for every online video. It worked for cigarette packs.

This is GLM 5.2 Max. GLM 5.2 High which use less than half[1] the tokens.

[1] https://z.ai/blog/glm-5.2

Qwen 27b is a compute heavy dense model.

Does this translate into a similar reduction in compute?

What's the catch?

equals 2 or 3 human brains in power usage. Amazing work!

It's fascinating that a $999 Mac Mini (M4 32GB) with almost similar wattage as a human brain gets us this far.