Z.ai GLM-Legal 超越 Claude Fable 5 與 Kimi K3，登頂 Harvey LAB 法律評測

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%.(function(){var f=document.

getElementById("mtp-glmlegal-frame");window.addEventListener("message",function(e){if(e.source===f.contentWindow&&e.data&&e.data.mtpFrame==="glm-legal"&&e.data.h){f.style.height=e.data.

h+"px"}})})(); #mtp-glmlegal-wrap p:empty,#mtp-glmlegal-wrap hr,#mtp-glmlegal-wrap del,#mtp-glmlegal-wrap s{display:none!important} How does GLM-Legal compare with Kimi K3, Claude Fable 5 and GPT-6 Astra?GLM-LegalGLM-5.3-Flash (base)Kimi K3Claude Fable 5GPT-6 AstraDeveloperZ.aiZ.

aiMoonshot AIAnthropicOpenAITotal / active paramsBuilt on 320B / 18B base320B / 18B2.8T / 104BNot disclosedNot disclosedContext window1M1M1M1M1MWeights / licenseNo public weightsOpen, MITOpen, Kimi K3 LicenseProprietaryProprietaryHarvey LAB (task pass)19.17%6.67%12.92%11.25%5.42%LegalBench86.23%83.

93%86.21%88.56%Not listed by ValsLegal Research Bench41.83%45.19%46.15%49.52%39.42%Cost per Harvey LAB test$0.15$0.57$3.83$19.23$26.16Avg Harvey LAB duration1h12m52m17s13m58s26m53s24m49sAPI price (in / out, per 1M tokens)Not published$0.15 / $0.

50$3 / $15$10 / $50$10 / $50AccessAPI by applicationAPI, Hugging FaceAPI, Hugging FaceAPIAPI 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.