zAI's GLM 5.2 open-weights model automates and debugs reinforcement learning training across multi-node H100 clusters

GLM 5.2 keeps on winning

GLM 5.2 is emerging as the first open-weights model capable of handling meaningful autoresearch tasks, from debugging setup issues to running and comparing RL training experiments across multi-node H100 clusters.

The big caveat: it lacks image understanding, so unlike Opus or Fable, it has to analyze raw WandB data programmatically rather than visually interpreting charts.

Still: while we are waiting for the come back of. Fable 5, zAI really nailed it with GLM 5.2

@teortaxesTex despite little if any of state involvement, chinese labs are *shockingly* disciplined in terms of following the right long-term trajectory. no sora-style consumerslop distractions or clawing for market share from frontier labs.

@kimmonismus Yes all areas are covered just UI/UX is where it's struggling hopefully will get better at this also, rest all sorted.

@teortaxesTex base on my own current runs it is more powerful than sonnet but also it seems token hungry (for few relatively bounded tasks it used 60 million tokens and cost me 20$ , also it is prob the agent not model but can be tool usage effect i suppose )

@absenteewarlord @teortaxesTex 😒nah it’s just different company doing sora-style stuff (e.g., bytedance’s seedance)

@kimmonismus every time someone says open models can't compete, another release like this shows up

what a time

@kimmonismus image modality missing feels like a weird block but the research capability sounds legit

opens up some interesting synthetic data loops

@kimmonismus @kimmonismus sounds like a game changer for research workflows. Wonder if they'll add image capabilities next, that'd be a killer feature.

@teortaxesTex Great work from the team. Happy to discuss opportunities if you're interested 👏