CheckOps
OpenCompass
OpenCompass is an Apache-2.0 LLM evaluation platform from Shanghai AI Laboratory that benchmarks open and API models across large dataset collections with distributed evaluation.
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Introduction
OpenCompass is an LLM evaluation platform supporting a wide range of models, from OpenAI, Anthropic and Gemini APIs to open-source models served locally. It maintains large collections of datasets and publishes leaderboards.
Configurations define model and dataset combinations, and the platform partitions work across GPUs or clusters for efficient runs. It supports generation and perplexity-based evaluation, LLM-as-judge subjective evaluation, long-context and agent benchmarks, and inference backends such as vLLM and LMDeploy.
In the quality loop it is a model-level regression gate, particularly popular for evaluating Chinese and multilingual models.
The source code is at open-compass/opencompass on GitHub under the Apache-2.0 licence, with about 7,600 stars; the most recent commit was on 11 November 2026.
Features
- Many datasets: Broad benchmark collections.
- API and local models: Wide model support.
- Distributed runs: Partitioned evaluation.
- Subjective eval: LLM-judge evaluation.
- Acceleration: vLLM and LMDeploy backends.
- Leaderboards: Public results.
Pros
- Scale: Built for large evaluation sweeps.
- Free to use: Open source under the Apache-2.0 licence, so the core tool costs nothing to use.
- Actively maintained: The repository had commits as recent as 11 November 2026.
- Community: About 7,600 GitHub stars.
Cons
- Config complexity: Many options to learn.
- Documentation mix: Some resources are Chinese-first.
- Compute heavy: Large sweeps need GPUs.
Usage and Links (Example)
pip install opencompass
opencompass --models hf_internlm2_5_1_8b_chat --datasets demo_gsm8k_chat_gen
Resources:
Pricing
OpenCompass is free and open source under the Apache-2.0 licence.
Recommended for?
- Model developers running large benchmark sweeps.
- Teams evaluating multilingual models.
Conclusion
OpenCompass is a scalable benchmarking platform with broad model and dataset support.
Use it for model selection and regression, not application testing.
On CheckOps, OpenCompass is filed under the Release & CI gates stage. Related tools listed here include LM Evaluation Harness, Lighteval, HELM, Inspect, OpenAI Evals and DeepEval. When comparing them, weigh the licence, the languages and platforms each supports, whether it is self-hosted or managed, and how cleanly it slots into your existing CI pipeline. Details on this page were checked against the official website, documentation and repository on 11 November 2026.
Alternatives
Other tools on CheckOps that cover similar ground. Open a page, or compare one with OpenCompass side by side.
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HHELMHELM (Holistic Evaluation of Language Models) is an Apache-2.0 framework from Stanford CRFM for reproducible, transparent evaluation of language models across many scenarios and metrics; it entered maintenance mode in June 2026.Compare with OpenCompass
IInspectInspect is the UK AI Security Institute's MIT-licensed framework for LLM evaluations, with datasets, solvers, scorers, agents, sandboxed tools and 200+ pre-built evals.Compare with OpenCompass
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