The AI industry has spent years chasing bigger context windows, but a funny thing happens when you actually fill them: most models lose the plot. Accuracy degrades past a few hundred thousand tokens, long-running agents drift off course, and what looked like a superpower turns into an expensive hallucination machine.
It has released by Z.ai under an MIT open-source license, especially for the kind of long-horizon coding work where most AI agents currently fall apart.
Solid 1M Context: A solid 1M-token context that stably sustains long-horizon work
Advanced Coding with Flexible Effort: Stronger coding capabilities with multiple thinking effort levels to balance performance and latency
Improved Architecture: It proposes IndexShare, which reuses the same indexer across every four sparse attention layers, reducing per-token FLOPs by 2.9× at a 1M context length. It also improves GLM-5.2’s MTP layer for speculative decoding, increasing the acceptance length by up to 20%
Pure Open: An MIT open-source license — no regional limits, technical access without borders
Capabilities :
It can design and build 3D UI/UX websites with interactive elements.
It can create games, generate code, and develop complete applications.
It can debug and optimize existing code efficiently.
It can also assist with research, automation, problem-solving, and large-scale software projects.
GLM-5.2 shows massive gains compared to its predecessor GLM-5.1.On Terminal-Bench 2.1GLM-5.2 is now the strongest open-source model on standard coding tests. But more importantly, it's breathing down the neck of the industry leaders.
Full Benchmark Table
