Z.ai's coding and agent model, released August 14, 2026. It reuses the same 743B-parameter base as GLM-5.2 and gets its gains entirely from scaled post-training, with a 1-million-token context and a jump in long-horizon coding and cybersecurity work.
Last verified · 2026-10-23 · by Moe Ameen
Published 2026-08-24 · Updated
Short answer
GLM-5.3 is Z.ai's coding and agent model, released August 14, 2026. It uses the same 743B-parameter base as GLM-5.2, and every gain comes from more post-training. Z.ai reports Terminal-Bench 3.0 rising from 4.6 to 28.3 and CyberGym reaching 84.5%. It has a 1M-token context and always reasons. It is text only, and open weights are now on Hugging Face.
Key takeaways
GLM-5.3 is a large language model from Z.ai — the Chinese lab formerly known as Zhipu AI — released on August 14, 2026. It is aimed squarely at complex coding, long-running agent tasks, and cybersecurity analysis rather than at chat or content.
The notable part of the release is how it was made: Z.ai says GLM-5.3 uses the same base model as GLM-5.2, and every reported gain comes from larger-scale post-training — more task environments, more environment types, and longer training runs — not from retraining the base. The base is a mixture-of-experts model with roughly 743 billion total parameters and about 40 billion active per step.
The benchmark jumps it claims are large. On Terminal-Bench 3.0, an agentic command-line benchmark, Z.ai reports 28.3 for GLM-5.3 against 4.6 for GLM-5.2; on DeepSWE v1.1 it reports 66.9, up from 46.2. On security-focused tests it cites CyberGym at 84.5% and ExploitBench at 54.4% (up from 24.4%). Z.ai also disclosed that its cybersecurity capability "developed faster than we expected," and that in testing with security teams the model produced thousands of vulnerability findings across hundreds of real codebases: after review, 2,436 vulnerabilities across 269 projects, including 1,097 medium-to-high severity issues.
On access and shape: GLM-5.3 is a text-in, text-out model with a 1-million-token context window and support for long outputs. It exposes reasoning-effort levels (low, high, and max), and unlike GLM-5.2, thinking cannot be turned off — a breaking API change for anyone migrating. At launch it was available through the Z.ai API and the GLM Coding Plan (with a ZCode agent environment), and Z.ai said it would publish open weights about two weeks after launch, once safety evaluation and hardening finished. The weights are now listed on Hugging Face as zai-org/GLM-5.3. Check Z.ai's pricing page for current Coding Plan and API rates before you depend on a number.
GLM-5.3's real edge is not writing a caption — it is reasoning across a huge input and executing long, multi-step work. Feed it a full webinar transcript, a quarter of support tickets, or a messy strategy doc inside its million-token context and it will come back with a coherent slate of angles, scripts, and hooks. That is a genuinely strong front end for a creator. But it ends at text on a screen: no face, no video, no carousel, no schedule, no post. That handoff is exactly where Kompozy starts, and it is a different job than the one the model does.
Take GLM-5.3's slate of scripts and drop the strongest into Kompozy as a source. From that single input Kompozy generates a full set of finished assets: a captioned Persona Short with a face-locked HeyGen avatar, a brand-exact Carousel, quote graphics pulled from the copy, photo posts, a full blog article, and an email newsletter — each rewritten under a Persona Brief so the voice stays yours instead of reading like raw model output. Then Autopilot schedules and publishes the set across the eight social platforms plus blog and email, every asset clearing a per-post review gate first. If you are technical enough to run GLM-5.3 as an agent, you can also let it write the automation that pulls new source material in on a cadence, and let Kompozy turn each batch into a week of on-brand posts. The model reasons and drafts at the front; Kompozy builds the identity and ships it to an audience.
A real persona short rendered in the Kompozy workspace. We did not make it about GLM-5.3. It is here so you can see what the format looks like when it comes out finished.
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GLM-5.3 is a large language model from Z.ai (formerly Zhipu AI), released August 14, 2026, built for complex coding, long-horizon agent tasks, and cybersecurity analysis. It reuses the same 743B-parameter base as GLM-5.2 and gets its gains entirely from scaled post-training, with a 1-million-token context window.
Z.ai kept the same base model and improved GLM-5.3 purely through larger-scale post-training. It reports big jumps on agentic and coding benchmarks — for example Terminal-Bench 3.0 at 28.3 versus 4.6, and DeepSWE v1.1 at 66.9 versus 46.2 — plus stronger cybersecurity results. One breaking change: unlike GLM-5.2, thinking cannot be disabled.
No. GLM-5.3 is a text-in, text-out model focused on coding, reasoning, and agent tasks — it produces text and code only, not images, video, or audio. To turn its scripts and ideas into visual content you pair it with a generation-and-publishing engine like Kompozy.
At launch GLM-5.3 was available through the Z.ai API, the GLM Coding Plan, and ZCode. Open weights followed after safety evaluation and are now on Hugging Face, so you can also self-host. Check Z.ai's pricing page for current Coding Plan and API rates.
Draft the script in GLM-5.3, then bring it into Kompozy as a source. Kompozy generates a full set of formats from that one input — persona/avatar video, carousels, quote graphics, photo posts, a blog, and a newsletter — holds a consistent face and voice across them, and schedules and publishes across the eight social platforms plus blog and email.
We checked every figure and product claim on this page against the sources listed below on 2026-10-23, and removed or corrected anything they did not support. Benchmark figures are Z.ai's own reported results, not our tests. Kompozy plan and platform details come from kompozy.io/pricing and kompozy.io.
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