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AI Evaluation & Observability

ReLE

ReLE is a Chinese-language large language model benchmarking project that publishes capability rankings across seven domains and roughly 300 evaluation dimensions, alongside a large model-defect catalog.

Independent OpenViST project profile, based on linked sources.

ReLE — OpenViST project profile in AI Evaluation & Observability.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use ReLE when selecting a benchmark area for Chinese-language model comparison or when researching failures that may be obscured by an overall score.

Who it is for

  • Researchers comparing language-model performance on Chinese-language tasks.
  • Teams investigating model failures across specialized subject areas.
  • Organizations interested in evaluation of a private model through the ReLE benchmark team.

Documented uses

  • Compare models on a specific domain or fine-grained task rather than only broad capability.
  • Find evaluation areas such as education, healthcare, finance, law, reasoning, language, and tool use.
  • Investigate recurring failures using the project's model-defect catalog.
Before you choose

Requirements & limits

  • Rankings are divided by domain and detailed dimensions, so select the task area relevant to your evaluation.
  • The README describes both commercial and open-source model coverage; listed models and entries can change as the project is updated.
  • Evaluation of private models is presented as a contact-based service, not a documented self-service workflow.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Explore ReLE model rankings by evaluation area

Compare published Chinese-language model rankings across ReLE’s listed evaluation areas.

Before you start

  • A web browser and access to the ReLE project README.

Steps

  1. Open the ReLE project README.

  2. Use its table of contents to locate the overall or domain-specific ranking section, such as education, healthcare, finance, law, reasoning, language, or agent and tool use.

  3. Review the published ranking for the area relevant to your comparison.

Expected outcome

A comparison based on the selected published ranking and evaluation area.

Guide limitations

  • The README describes published rankings; these steps do not run an evaluation of a model.
  • The rankings and included models are updated over time.
Source-based practical guide

Request an evaluation for a private model

Contact the ReLE benchmark team to request evaluation of a private model.

Before you start

  • A private model to be evaluated.
  • A way to contact the ReLE benchmark team through the README’s linked contact option.

Steps

  1. Open the ReLE project README.

  2. Find the section offering evaluation for private models.

  3. Use the linked contact option to contact the ReLE benchmark team about an evaluation.

Expected outcome

A contact request to the ReLE benchmark team about evaluating a private model.

Guide limitations

  • The README does not specify the evaluation procedure, requirements, timeline, or results; contact is the documented next stage.
Evidence and transparency

Sources & review

Source record details
Source availability
Active
Sources checked
16 October 2026
Original website title
jeinlee1991/chinese-llm-benchmark · Official homepage title · retained in its source language