Z.ai's GLM-Legal AI Achieves High Scores on Legal Benchmark

The model is built on Z.ai's GLM-5.3-Flash architecture and has achieved a 19.2% all-pass rate on Harvey’s Legal Agent Benchmark (LAB). This rate is nearly three times higher than its base model's 6.7% pass rate.

GLM-Legal is a domain-specialized version of Z.ai's GLM-5.3-Flash model, which is natively multimodal and can process text, images, video, and files, outputting text. The base model features 320 billion total parameters with 18 billion active parameters, utilizing a mix of sparse and linear attention to reduce serving costs for long contexts.

The model underwent a two-stage training process. The first stage involved mid-training on expanded legal corpora to enhance reasoning from facts to conclusions. The second stage included post-training with reinforcement learning across tens of thousands of legal task environments, with the agent harness co-evolving with the model.

Performance metrics indicate GLM-Legal achieved a 19.17% Harvey LAB task pass rate, ranking seventh out of 79 models on Vals AI, at a cost of $0.15 per test. While its performance on Vals AI’s Legal Research Bench was 41.83%, below its base model's 45.19%, Z.ai states GLM-Legal offers frontier-class legal agent scores at approximately 1/128 the cost of Claude Fable 5.

Access to GLM-Legal is currently limited, with its API available only through application. Public weights are not provided, and the model runs exclusively on Z.ai’s hosted API.