Z.ai GLM-Legal Beats Claude Fable 5 and Kimi K3 on Harvey LAB

Z.ai just released GLM-Legal . GLM-Legal is a legal AI model from Z.ai, built on GLM-5.3-Flash and trained for agentic legal work. It targets contract review, evidence analysis and compliance research. The key result is a 19.2% all-pass rate on Harvey’s Legal Agent Benchmark (LAB) . That is nearly 3x its base model’s 6.7%. For developers, the catch is access: the API is application-only for now. TL;DR Size: Built on GLM-5.3-Flash, a 320B-total, 18B-active MoE with a 1M-token context and 128K max output. Z.ai lists no separate GLM-Legal parameter count. Runs on: Z.ai’s hosted API only, by application. No public weights. The base model self-hosts on multi-GPU servers via vLLM or SGLang, with FP8 weights. Performance: Top-10 on Harvey LAB at a fraction of frontier cost. Within 2.3 points of the LegalBench leader. Best: 19.17% Harvey LAB task pass rate, #7 of 79 on Vals AI, at $0.15 per test. Worst: 41.83% on Vals AI’s Legal Research Bench, below its own base model (45.19%). Bottom line: Best: frontier-class legal agent scores at about 1/128 the cost of Claude Fable 5. Worst: gated beta with no price, no weights and slow runs (1h12m per task). What is GLM-Legal? GLM-Legal is a domain-specialized version of GLM-5.3-Flash for law firms, in-house counsel and compliance teams. The base is Z.ai’s first natively multimodal GLM-5 model . It has 320B total parameters with 18B active. It mixes sparse and linear attention to cut long-context serving cost. It reads text, images, video and files, and outputs text. How was GLM-Legal trained? Training ran in 2 stages: Mid-training on expanded legal corpora, to strengthen reasoning from facts to rules to conclusions. Post-training with reinforcement learning across tens of thousands of legal task environments . The Z.ai team also describes the agent harness co-evolving with the model during post-training. Edge cases in training exposed harness bottlenecks. Harness fixes then exposed the model to more realistic constraints. How does GLM-Legal score on Harvey’s Legal Agent Benchmark? Harvey LAB is an open-source benchmark of 1,250 tasks across 24 practice areas . Over 75,000 expert-written rubric criteria grade the work. A task passes only if every criterion passes. Harvey calls this all-pass grading. Vals AI runs the held-out set with 2 LLM judges and internet disabled . Agents get file tools plus docx , pptx and xlsx skills. On that leaderboard, GLM-Legal scores 19.17% and ranks #7 of 79. Its base, GLM-5.3-Flash, scores 6.67%. The 12.5-point lift is the core claim, and an independent evaluator reproduced it. Z.ai’s launch chart shows GLM-Legal ahead of Kimi K3 (12.92%), Claude Fable 5 (11.25%) and GPT-6 Astra (5.42%). Those figures match Vals AI. The chart omits 6 models ranked higher, led by Muse Spark 1.2 at 25.42%. GLM-Legal also passes 92.5% of individual criteria. Top models sit near 90% to 95% on that measure. Does GLM-Legal match frontier models on LegalBench? Roughly. Z.ai claims parity on LegalBench and the Chinese-focused PLawBench without publishing numbers. Vals AI scores GLM-Legal at 86.23% on LegalBench . Claude Fable 5 leads at 88.56% . Kimi K3 scores 86.21% . How does GLM-Legal compare with Kimi K3, Claude Fable 5 and GPT-6 Astra? All benchmark scores, costs and durations are from Vals AI’s runs as of October 12, 2026. Vals ran both GLM models at $0.075 / $0.25 per 1M tokens. How can developers access GLM-Legal? Law firms, legal-tech companies and in-house teams can apply for API access . Z.ai has published no price. No GLM-Legal repository exists on Hugging Face as of October 13, 2026. Z.ai says GLM-Legal will come to AutoClaw , its desktop agent app, but gave no date. The base model is available today at $0.15 / $0.50 per 1M tokens . Teams can prototype pipelines on it, then swap the model ID later. Key Takeaways GLM-Legal scores 19.17% on Harvey LAB, up from 6.67% for its base. It ranks #7 of 79 on Vals AI, behind 6 Meta and Google models. It costs $0.15 per Harvey LAB test, versus $19.23 for Claude Fable 5. Legal Research Bench dropped 3.36 points versus GLM-5.3-Flash. Access is application-only, with no published price or weights. Check out the Z.ai tech blog , the Vals AI Harvey LAB leaderboard and the GLM-5.3-Flash model card . Apply for API access here .. All credit goes to the researcher of this project. Also, feel free to follow us on Twitter and don’t forget to join our 150k+ML SubReddit and Subscribe to our Newsletter . Wait! are you on telegram? now you can join us on telegram as well. The post Z.ai GLM-Legal Beats Claude Fable 5 and Kimi K3 on Harvey LAB appeared first on MarkTechPost .