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zai-org-glm-5-3-flash
GLM-5.3-Flash is a native multimodal model from Z AI built for efficient coding and long-horizon agent tasks. With 320 billion total parameters and just 18 billion active, it outperforms GLM-5.2 across benchmarks at a fraction of the cost while approaching Claude Opus 4.8 on coding and agentic tasks.
It is the first multimodal model in the GLM-5 series, combining sparse and linear attention in a hybrid architecture that cuts long-context serving costs. Reasoning is always on and cannot be disabled; the reasoning_effort parameter accepts low, high, and max, with max as the default. Weights are published under an MIT license.
Fine-tuning trains an adapter over attention while the routed experts stay frozen in 4 bits, so a fine tune of this model costs about what a far smaller one would.
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