
Z.ai launches GLM-5.3, pitching it as a strong open-weights coding model with improved token efficiency.
Chinese AI lab Z.ai released GLM-5.3, a 743-billion parameter coding model focused on token efficiency and high performance across benchmarks.
AI-generated summary
Z.ai is a Beijing-based artificial intelligence lab currently listed on the U.S. Entity List.
Chinese AI lab Z.ai released GLM-5.3 on Thursday, a sizable coding model it's pitching as the strongest open-weights coder on the market. The model is live now through the GLM Coding Plan subscription and ZCode, with API access and downloadable weights following after a safety review.
"Scaling post-training is all we did for GLM-5.3," the company wrote in its launch post. "With GLM-5.2 we built the stack... Over the past month we kept scaling on this stack: more environments, more diverse tasks, and more compute spent training on them."
The team focused more on token efficiency, not raw dominance. GLM-5.3 stands at 743 billion parameters and consumes a lot less tokens per task than its predecessor. Parameters are the amount of dials a model handle while processing information while tokens are the basic unit of information a model can consume or generate.
Z.ai says GLM-5.3 clears 34.5% on its in-house Z.ai Code Bench at Max effort while burning roughly 75,000 output tokens per task, against GLM-5.2's 23.4% at 96,000. Against closed models, the blog notes it beats Claude Opus 4.8 on token economy but "remains behind Claude Fable 5, which reaches 39.5% at Max effort."
In terms of coding, GLM5.3 is a very good performer, beating fellow Chinese model Kimi K3 on the most relevant benchmarks.
On Terminal Bench 3.0—a test of autonomous shell/tool use in real Linux environments—GLM-5.3 scores 28.3, slightly behind closed models Fable 5 (33.7) and GPT-5.6 Sol (34.6). On DeepSWE v1.1, a benchmark for fixing real GitHub issues end-to-end, open rival Kimi K3 (67.5) and Fable 5 (69.7) both beat GLM-5.3's 66.9.
The pattern can be more or less summed up like this: GLM-5.3 clears its own predecessor and some open peers, but closed U.S. models still lead the headline coding boards.
The cybersecurity results show another important leap. GLM-5.3 leads CyberGym at 84.5% and more than doubles GLM-5.2 on exploitation benchmarks. Z.ai says the model flagged 2,436 vulnerabilities across 269 open-source projects, 1,097 of them medium-to-high severity.
"GLM-5.3 takes agentic coding to the next level, delivering a dramatic improvement over GLM-5.2 while achieving better results with fewer output tokens," Z.ai posted on X. "GLM-5.3 is available now through GLM Coding Plan and ZCode. API access and open weights will be released in stages following rigorous safety evaluations."
On price, the gap with U.S. frontier models is the open-weights draw. Z.ai's GLM Coding Plan runs on a points quota (off-peak calls cost half), with Zhipu's API priced at roughly a tenth of U.S. frontier per-token rates—GLM-5.2's official rate was $1.40 in / $4.40 out per million tokens. That stacks against GPT-5.3-Codex at $1.75 / $14 and Claude Opus 4.8 near the top of Anthropic's tiers.
Z.ai is a Beijing lab included on the U.S. Entity List, which means American firms cannot export controlled tech to it. Despite this, GLM is an extremely popular model and Chinese open-weight models already beat American ones on OpenRouter token usage.
GLM-5.3 weights are set for public release in about two weeks, per the launch post—the open-weights label applies to what's coming, not what's downloadable today.
AI outlook — possibilities, not facts
GLM-5.3 weights set for public release in about two weeks
Likely · Within weeks

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