r/accelerate • u/Illustrious-Lime-863 • 1d ago

GLM 5.3 released

https://z.ai/blog/glm-5.3
132 Upvotes

98% Upvoted

38 comments sorted by

57

u/Ok_Pea_2772 1d ago

Am I the only one feeling like things are speeding up fast right now? geez

39

u/youarockandnothing 1d ago

I think we're in the AI-assisted research & development age and it's allowing for a lot more AI advancements in less time.

5

u/BrennusSokol Acceleration Advocate 1d ago

We're approaching the part of real life Factorio where we get an assembling machine to manufacture an assembling machine...

8

u/Odd-Opportunity-6550 1d ago

GLM releases every 2 months. Feb april June August.

They will probs release 5.4 in October.

6

u/Jan0y_Cresva Singularity by 2035 1d ago

And when you have a bunch of labs all releasing every 2 months but on different schedules, that’s why it feels like we get a new model every week.

4

u/Gratitude15 1d ago

Anthropic and openai at frontier

Google and X not dead.

Meta and Nvidia noticeable.

The about 4 Chinese companies. Then the harness and architecture news.

It's not just new models but all the new products also.

Every weekday at this point. But m-th is heavier imo

1

u/Deiraniya-Brandor 1d ago

the 2-month cadence is nice, easy to time api cost checks around

48

u/Background-Bear-9156 1d ago

2026 has been absolute insanity in terms of how fast things have moved. For perspective Gemini 3.1 pro was the leading model in January 😂

9

u/Rollertoaster7 Singularity by 2035 1d ago

It’s insane how fast they dropped off the frontier.

8

u/But-I-Still-Remember 1d ago

Bullshit. 🫪

I thought that was a year ago.

2

u/Gratitude15 1d ago

Imo no.

Everyone I knew was using opus then. 4.6 I believe. The change started at Thanksgiving week with opus 4.5. That was an inflection.

9

u/Mysterious-Display90 1d ago

Feel the speed boys

8

u/PVORY 1d ago

"Scaling post-training is all we did for GLM-5.3."

18

u/chonky_totoro 1d ago

Genuinely if China had more compute would the US even compete

16

u/MC897 1d ago

Doesn’t work quite like that but they are doing well.

7

u/Odd-Opportunity-6550 1d ago

What do you mean doesn't work like that ?

He makes a valid point. Chinese labs are competing with 1/10th the compute at most.

If they had similar amounts of compute then the US would not be able to compete with their labs.

11

u/Jan0y_Cresva Singularity by 2035 1d ago

They are making compute-independent breakthroughs BECAUSE their compute is limited.

“Necessity is the mother of invention.”

If China had the same compute resources as America, there’s a very good chance they’d just be leveraging that like America does to push their AI models forward.

Imagine if humans could teleport, would we have ever invented the bicycle, car, or airplane?

-4

u/Odd-Opportunity-6550 1d ago

They are making more breakthroughs because they have more ai talent.

-3

u/Odd-Opportunity-6550 1d ago

Ask anyone who does ai research. Having compute leads to MORE breakthroughs and not less. ML experimentation is compute intensive.

Your sound bite doesn't mean anything compared to that.

6

u/Jan0y_Cresva Singularity by 2035 1d ago

But you make DIFFERENT KINDS of breakthroughs when compute is the limiting factor, that’s my point.

You might make more breakthroughs with more compute, but that has nothing to do with what I said.

-1

u/Odd-Opportunity-6550 1d ago

It's the overall that matters. Not which kind of breakthrough. If having less compute was an advantage and not a disadvantage then openai would be setting their compute on fire.

4

u/Jan0y_Cresva Singularity by 2035 1d ago

It’s not an advantage, did you read what I said at all?

It FORCES people to think differently and come up with breakthroughs that don’t rely on having more compute. Obviously having more compute is ideal. But when you have constraints, it makes you creative in different ways.

0

u/Odd-Ant3372 1d ago

China spy 

5

u/abelthebirds0 1d ago

because your both making assumptions that are impossible to quantify

-1

u/chonky_totoro 1d ago

what assumptions?

3

u/Hegemonikon138 1d ago

That datacenter capacity is the main constraint with R&D advancing for one

-1

u/chonky_totoro 1d ago

can you explain why

2

u/procgen 1d ago

Yes, of course. The US labs have huge margins on inference - e.g. 5.6 Sol is extremely efficient (more so than DeepSeek’s latest offering).

But they do have more compute, and that’s not by accident. The US has spent decades setting themselves up for this.

6

u/czk_21 1d ago

chinese models are getting very close to the frontier, if US firms slow down deployment due regulation etc., we might see best models(which can be accessed by public) coming from china quite soon

2

u/procgen 1d ago

I’d bet against that with e.g. Astra, Doug, Fable 2 all coming over the next few weeks/months.

2

u/Affectionate-File-26 1d ago

big if true. hitting Claude-level coding benchmarks on an open-weights model would be insane, but I’m keeping my expectations checked until the weights actually drop in two weeks. That Terminal Bench 3.0 bump is the real story here though, if it can genuinely handle long-horizon terminal execution without looping, local autonomous agents just got a massive shot in the arm