Earlier quoted context omitted.
My local tennis court's reservation website was broken and I couldn't cancel a reservation, and I asked GLM-5.1 if it can figure out the API. Five minutes later, I check and it had found a /cancel.php URL that accepted an ID but the ID wasn't exposed anywhere, so it found and was exploiting a blind SQL injection vulnerability to find my reservation ID. Overeager, but I was really really impressed.
Yeah it seems they did not align it to much, at least for now. Yesterday it helped me bypass the bot detection on a local marketplace. that i wanted to scrap some listing for my personal alerting system. Al the others failed but glm5.1 found a set of parameters and tweaks how to make my browser in container not be detected.
GLM-5.1: Towards Long-Horizon Tasks
101–110 of 285 posts
Re: GLM-5.1: Towards Long-Horizon Tasks
#102It's an okay model. My biggest issue using GLM 5.1 in OpenCode is that it loses coherency over longer contexts. When you crest 128k tokens, there's a high chance that the model will start spouting gibberish until you compact the history. For short-term bugfixing and tweaks though, it does about what I'd expect from Sonnet for a pretty low price.
I wonder if running the compaction in a degraded state produces a subpar summary to continue with.
Re: GLM-5.1: Towards Long-Horizon Tasks
#103It's an okay model. My biggest issue using GLM 5.1 in OpenCode is that it loses coherency over longer contexts. When you crest 128k tokens, there's a high chance that the model will start spouting gibberish until you compact the history. For short-term bugfixing and tweaks though, it does about what I'd expect from Sonnet for a pretty low price.
Chiming in to second this issue. It is wildly frustrating. I suspect that this isn't the model, but something that z.ai is doing with hosting it. At launch I was related to find glm-5.1 was stable even as the context window filled all the way up (~200k). Where-as glm-5, while it could still talk and think, but had forgotten the finer points of tool use to the point where it was making grevious errors as it went (burn…
Re: GLM-5.1: Towards Long-Horizon Tasks
#104It's an okay model. My biggest issue using GLM 5.1 in OpenCode is that it loses coherency over longer contexts. When you crest 128k tokens, there's a high chance that the model will start spouting gibberish until you compact the history. For short-term bugfixing and tweaks though, it does about what I'd expect from Sonnet for a pretty low price.
Chiming in to second this issue. It is wildly frustrating. I suspect that this isn't the model, but something that z.ai is doing with hosting it. At launch I was related to find glm-5.1 was stable even as the context window filled all the way up (~200k). Where-as glm-5, while it could still talk and think, but had forgotten the finer points of tool use to the point where it was making grevious errors as it went (burn…
Re: GLM-5.1: Towards Long-Horizon Tasks
#105Re: GLM-5.1: Towards Long-Horizon Tasks
#106Not only did this one draw me an excellent pelican... it also animated it! https://simonwillison.net/2026/Apr/7/glm-51/
Re: GLM-5.1: Towards Long-Horizon Tasks
#107Earlier quoted context omitted.
These comments are probably either by friends of the OP or perhaps associated with the project somehow, which is against HN's rules but not the kind of attack we're mostly concerned with these days. Old-fashioned voting rings and booster comments aren't existential threats and actually bring up somewhat nostalgic feelings at the moment! Thanks for watching out for the quality of HN...
Would love to read a Tell HN post about the kinds of attacks you are concerned with!
These are different from the submitter-passed-a-link-to-friends kind of upvoting and booster comments, which feel quaint by comparison. In this case people usually don't know they are breaking HN's rules, which is why they don't try to hide it.
Re: GLM-5.1: Towards Long-Horizon Tasks
#108Re: GLM-5.1: Towards Long-Horizon Tasks
#109Earlier quoted context omitted.
For conversational purposes that may be too slow, but as a coding assistant this should work, especially if many tasks are batched, so that they may progress simultaneously through a single pass over the SSD data.
Three hour coffee break while the LLM prepares scaffolding for the project.