BlogLLM Benchmark Scores as Published, Side by Side
PLawBench: Results as Published
Every result the catalog holds for PLawBench: 5 models from 3 developers, read from 1 page. Each number is as printed by the company named beside it; nothing is ranked or rescored. Models are listed by developer, newest first.
Area Knowledge WorkMaintainer Alibaba GroupIntroduced 2026Data version 2026103001, as of 2026-10-30
PLawBench tests large language models on Chinese legal practice across 13 scenarios that follow a lawyer's workflow: public legal consultation, practical case analysis and drafting legal documents. It has 850 questions, and each has expert-written rubrics, about 12,500 items in total. An LLM evaluator aligned with human expert judgments scores each response against those rubrics.
PLawBench
| Model | Value | Printed by | Setup as printed |
|---|---|---|---|
| GPT-5.6 SolOpenAI, released 2026-07-09 | 72.3 | Alibaba, Qwen3.8-Max comparisonchecked 2026-10-14 | Effort: max |
| Claude Fable 5Anthropic, released 2026-06-09 | 70.2 | Alibaba, Qwen3.8-Max comparisonchecked 2026-10-14 | - |
| Claude Opus 4.8Anthropic, released 2026-05-28 | 69.6 | Alibaba, Qwen3.8-Max comparisonchecked 2026-10-14 | - |
| Qwen3.8-MaxAlibaba, released 2026-08-03 | 73.2 | Alibaba, Qwen3.8-Max comparisonchecked 2026-10-14 | - |
| Qwen3.7-MaxAlibaba | 58.9 | Alibaba, Qwen3.8-Max comparisonchecked 2026-10-14 | - |
Every number here is read from the same catalog file as the benchmark table, data version 2026103001, and is the number the table shows for that model and test. Where one page printed a model under several setups, each value is listed. The catalog is public in armanobosyan/sugra-llm-benchmarks; a wrong number can be reported from the table, with Report an error under the value, or as an issue in that repository.