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z.ai's open source GLM-5 achieves record low hallucination rate and leverages new RL 'slime' technique

GLM-5 features 744 billion parameters, achieves record-low hallucination rates, and offers cost-effective AI coding and agentic workflows with open-source MIT licensing.

  • Today Zhipu AI released GLM-5, a fifth-generation open-weight model available on its site, GitHub, Hugging Face, and live on OpenRouter on February 11, 2026.
  • Positioning GLM-5 as a tool, Zhipu argues it shifts from `vibe coding` to `agentic engineering`, offers MIT license and open weights to avoid vendor lock-in, and trains fully on Huawei Ascend chips for `full independence`.
  • Doubling to 744 billion parameters, GLM-5 expands pre-training to 28.5 trillion tokens and uses a Mixture-of-Experts with 40B active parameters plus DeepSeek Sparse Attention preserving 200K context.
  • Following the launch, Zhipu raised its GLM Coding Plan price by 30pc and Hong Kong-listed Zhipu shares jumped 30%, while the 744B parameter scale creates deployment and governance hurdles.
  • Using APRIL, the new RL stack `slime` and a 35-point improvement on the AA-Omniscience Index led GLM-5 to a record-low hallucination rate, according to Artificial Analysis.
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WebProNews broke the news in on Wednesday, February 11, 2026.
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