GLM-5.1: Towards Long-Horizon Tasks • Hacker News Board

Re: GLM-5.1: Towards Long-Horizon Tasks

#141

Post by hodgehog11 » Wed, Apr 08, 2026, 1:04 AM UTC

dvt wrote: post #118

Every single day, three things are becoming more and more clear: (1) OpenAI & Anthropic are absolutely cooked; it's obvious they have no moat (2) Local/private inference is the future of AI (3) There's *still* no killer product yet (so get to work!)

(1) is absolutely not true if you actually use these models on a regular basis and include Google in here too. The difference in reliability beyond basic tasks is night and day. Their reward function is just so much better, and there are many nuanced reasons for this.

(2) is probably true but with caveats. Top-tier models will never run on desktop machines, but companies should (and do) host their own models. The future is open-weight though, that much is for sure.

(3) This is so ignorant that others have already responded to it. Look outside of your own bubble, please.

Re: GLM-5.1: Towards Long-Horizon Tasks

#142

Post by chris_ivester » Wed, Apr 08, 2026, 1:12 AM UTC

allan_s wrote: post #133

jimmaswell wrote: post #120

Earlier quoted context omitted.

No killer product? Coding assistants and LLM's in general are the single most awe-inspiring achievement of humanity in my lifetime, technological or otherwise. They've already massively improved my and others' lives and they're only going to get better. If pre and post industrial revolution used to be the major binary delineation of our history, I'm fairly confident it will soon be seen as pre and post AI instead.

I've also been using the LLM in Posthog and it has been impressive. I need to check if I can also plug a MCP/Skill to my actual claude code so that I can cross reference the data from my other data source (stripe, local database, access logs etc.) for in depth analysis

This might be up your alley - have Posthog and a ton of other SaaS tools connected so you can run analysis across quant/qualitative data sources: https://dialog.tools

Re: GLM-5.1: Towards Long-Horizon Tasks

#143

Post by neonstatic » Wed, Apr 08, 2026, 1:21 AM UTC

dvt wrote: post #118

Every single day, three things are becoming more and more clear: (1) OpenAI & Anthropic are absolutely cooked; it's obvious they have no moat (2) Local/private inference is the future of AI (3) There's *still* no killer product yet (so get to work!)

The model is the killer product

Re: GLM-5.1: Towards Long-Horizon Tasks

#144

Post by neonstatic » Wed, Apr 08, 2026, 1:22 AM UTC

hodgehog11 wrote: post #141

dvt wrote: post #118

Every single day, three things are becoming more and more clear: (1) OpenAI & Anthropic are absolutely cooked; it's obvious they have no moat (2) Local/private inference is the future of AI (3) There's *still* no killer product yet (so get to work!)

(1) is absolutely not true if you actually use these models on a regular basis and include Google in here too. The difference in reliability beyond basic tasks is night and day. Their reward function is just so much better, and there are many nuanced reasons for this. (2) is probably true but with caveats. Top-tier models will never run on desktop machines, but companies should (and do) host their own models. The fut…

> Top-tier models will never run on desktop machines

Sorry, but you don't know that

Re: GLM-5.1: Towards Long-Horizon Tasks

#145

Post by marcus_holmes » Wed, Apr 08, 2026, 1:22 AM UTC

kcb wrote: post #119

dvt wrote: post #118

Every single day, three things are becoming more and more clear: (1) OpenAI & Anthropic are absolutely cooked; it's obvious they have no moat (2) Local/private inference is the future of AI (3) There's *still* no killer product yet (so get to work!)

What benefit is there to dropping $50k on GPUs to run this personally besides being a cool enthusiast project?

Why would anyone need more than 640Kb of memory?

Re: GLM-5.1: Towards Long-Horizon Tasks

#146

Post by CamperBob2 » Wed, Apr 08, 2026, 1:25 AM UTC

kcb wrote: post #119

dvt wrote: post #118

Every single day, three things are becoming more and more clear: (1) OpenAI & Anthropic are absolutely cooked; it's obvious they have no moat (2) Local/private inference is the future of AI (3) There's *still* no killer product yet (so get to work!)

What benefit is there to dropping $50k on GPUs to run this personally besides being a cool enthusiast project?

It will run exactly the same tomorrow, and the next day, and the day after that, and 10 years from now. It will be just as smart as the day you downloaded the weights. It won't stop working, exhaust your token quota, or get any worse.

That's a valuable guarantee. So valuable, in fact, that you won't get it from Anthropic, OpenAI, or Google at any price.

Re: GLM-5.1: Towards Long-Horizon Tasks

#147

Post by marcus_holmes » Wed, Apr 08, 2026, 1:33 AM UTC

plandis wrote: post #72

airstrike wrote: post #29

Earlier quoted context omitted.

100k tokens it's basically nothing these days. Claude Opus 4.6M with 1M context windows is just a different ball game

Claude Opus can use a 1M context window but I’ve found it to degrade significantly past 250k in practice.

Seconded. I'm getting used to the changes that happen in the conversation now, and can work out when it's time for my little coding buddy to have a nap.

And Opus is absolutely terrible at guessing how many tokens it's used. Having that as a number that the model can access itself would be a real boon.

Re: GLM-5.1: Towards Long-Horizon Tasks

#148

Post by zozbot234 » Wed, Apr 08, 2026, 1:40 AM UTC

8dazo wrote: post #134

Just saw the Claude Mythos post. Not sure when it’s going public, but this feels like a real jump, not just incremental progress. Also waiting for the next GLM release coz specs are looking kind of insane.

Gemini and GPT have Deep Research models already, Mythos looks like much the same thing.

Re: GLM-5.1: Towards Long-Horizon Tasks

#149

Post by jjfoooo4 » Wed, Apr 08, 2026, 1:44 AM UTC

grafmax wrote: post #140

dvt wrote: post #118

Every single day, three things are becoming more and more clear: (1) OpenAI & Anthropic are absolutely cooked; it's obvious they have no moat (2) Local/private inference is the future of AI (3) There's *still* no killer product yet (so get to work!)

> no moat I'd like to think the superior product wins. But Windows still thrives despite widespread Linux availability. I think sometimes we can underestimate the resilience of the tech oligopolies, particularly when they're VC-funded.

VC can spend all the money in the world and it won't matter if the cost of switching providers is effectively zero.

If I want to switch from Windows to Linux, I have to reconsider a whole variety of applications, learn a different UX, migrate data, all sorts of annoyances.

When I switch between Codex and Claude Code, there is literally no difference in how I interact with them. They and a number of other competitors are drop in replacements for each other.

Re: GLM-5.1: Towards Long-Horizon Tasks

#150

Post by fwipsy » Wed, Apr 08, 2026, 1:46 AM UTC

dvt wrote: post #118

Every single day, three things are becoming more and more clear: (1) OpenAI & Anthropic are absolutely cooked; it's obvious they have no moat (2) Local/private inference is the future of AI (3) There's *still* no killer product yet (so get to work!)

No moat: yes. Cooked: no. It's a race. Why assume they're going to lose? It relies on (2) which is only true if AI usefulness plateaus at some level of compute. That's a huge claim to be making at this stage. (3) AI has lots of killer products already. The big one is filling in moats. Unrealized potential though for sure.