# LM Evaluation Harness vs Ragas

| Attribute | LM Evaluation Harness | Ragas |
|---|---|---|
| **vioscaleAI score** | 48.2 (35% (low)) | 54 (32% (low)) |
| activity.commits_last_30d | 57 | - |
| adoption.dependent_repos | 252 | 1 |
| adoption.github_stars | 14,221 | 15,838 |
| content.faq | `[{"answer":"A Python-based evaluation framework that enables testing of language models against 60+ standard academic benchmarks with support for various model formats, APIs, and custom evaluation metrics. It is indexed under AI Evals Testing.","source":"https://github.com/pricing","question":"What is LM Evaluation Harness?","confidence":0.6},{"answer":"LM Evaluation Harness is open source, so it can be self-hosted and used at no licence cost. It is released under the MIT licence. Pricing changes often, so verify at source before relying on it.","source":"https://github.com/pricing","question":"Is LM Evaluation Harness free to use?","confidence":0.6},{"answer":"LM Evaluation Harness supports a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://github.com/pricing","question":"What platforms does LM Evaluation Harness support?","confidence":0.6},{"answer":"Yes. LM Evaluation Harness can be deployed self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://github.com/pricing","question":"Can LM Evaluation Harness be self-hosted?","confidence":0.6},{"answer":"We have confirmed 5 integrations for LM Evaluation Harness, including Hugging Face, PyTorch, VLLM, GitHub and OpenAI-compliant APIs. This is what we could verify from public sources, so the vendor may support others we have not indexed.","source":"https://github.com/pricing","question":"What does LM Evaluation Harness integrate with?","confidence":0.6},{"answer":"Yes. LM Evaluation Harness is published under the MIT licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.","source":"https://github.com/EleutherAI/lm-evaluation-harness","question":"Is LM Evaluation Harness open source?","confidence":0.95}]` | `[{"answer":"A Python-based framework that evaluates RAG applications through automatic metrics covering faithfulness, relevance, and recall. Includes tools to synthetically generate test datasets customized for specific use cases, enabling developers to assess LLM application performance at both component and end-to-end levels. It is indexed under RAG Tools.","source":"https://ragas.io","question":"What is Ragas?","confidence":0.6},{"answer":"Ragas is open source, so it can be self-hosted and used at no licence cost. It is released under the Apache-2.0 licence. Pricing changes often, so verify at source before relying on it.","source":"https://ragas.io","question":"Is Ragas free to use?","confidence":0.6},{"answer":"Ragas supports a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://ragas.io","question":"What platforms does Ragas support?","confidence":0.6},{"answer":"Yes. Ragas can be deployed self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://ragas.io","question":"Can Ragas be self-hosted?","confidence":0.6},{"answer":"We have confirmed 3 integrations for Ragas, including LlamaIndex, LangSmith and OpenAI. This is what we could verify from public sources, so the vendor may support others we have not indexed.","source":"https://ragas.io","question":"What does Ragas integrate with?","confidence":0.6},{"answer":"Yes. Ragas is published under the Apache-2.0 licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.","source":"https://github.com/vibrantlabsai/ragas","question":"Is Ragas open source?","confidence":0.95}]` |
| deployment.options | `{"self_hosted":true}` | `{"self_hosted":true}` |
| description.long | A framework for conducting few-shot evaluation of language models against various tasks and benchmarks. Supports multiple model backends, custom evaluation metrics, and extensible task definitions for assessing model capabilities and performance. | A Python-based framework that evaluates RAG applications through automatic metrics covering faithfulness, relevance, and recall. Includes tools to synthetically generate test datasets customized for specific use cases, enabling developers to assess LLM application performance at both component and end-to-end levels. |
| features.capabilities | `{"pricing_model":"free_open_source","architecture_model":"open_source_cli","multi_model_side_by_side_ab_regression_testing":true}` | `{"open_source":true,"pricing_model":"free_open_source","architecture_model":"open_source_cli","built_in_rag_eval_metrics":true,"llm_as_a_judge_prompt_grading_framework":true,"synthetic_test_dataset_generation_from_documents":true}` |
| integrations.count | 5 | 3 |
| integrations.list | `[{"name":"Hugging Face"},{"name":"PyTorch"},{"name":"VLLM"},{"name":"GitHub"},{"name":"OpenAI-compliant APIs"}]` | `[{"name":"LlamaIndex"},{"name":"LangSmith"},{"name":"OpenAI"}]` |
| language.primary | Python | Python |
| license.spdx | MIT | Apache-2.0 |
| platform.support | `{"cli":true,"mac":true,"linux":true,"windows":true}` | `{"cli":true}` |
| pricing | `{"type":"open_source","freeTier":true,"sourceUrl":"https://github.com/pricing","retrievedAt":"2026-10-14T22:30:23.897Z"}` | `{"type":"open_source","freeTier":true,"sourceUrl":"https://ragas.io","retrievedAt":"2026-08-21T13:52:19.928Z"}` |
| pricing.free_tier | yes | yes |
| pricing.model | open_source | commercial |
| pricing.price_level | free | free |
| pricing.transparent | yes | yes |
| release.cadence_days | 72 | 7 |
| release.history | `[{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.13","date":"2026-08-31T20:42:30Z","type":"stable","version":"v0.4.13"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.12","date":"2026-05-11T13:04:19Z","type":"stable","version":"v0.4.12"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.11","date":"2026-02-13T20:21:47Z","type":"stable","version":"v0.4.11"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.10","date":"2026-01-27T19:56:53Z","type":"stable","version":"v0.4.10"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.9.2","date":"2025-11-26T23:27:06Z","type":"stable","version":"v0.4.9.2"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.9.1","date":"2025-08-04T11:36:05Z","type":"stable","version":"v0.4.9.1"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.9","date":"2025-06-19T14:18:27Z","type":"stable","version":"v0.4.9"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.8","date":"2025-03-05T07:49:46Z","type":"stable","version":"v0.4.8"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.7","date":"2024-12-17T10:37:09Z","type":"stable","version":"v0.4.7"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.6","date":"2024-11-25T13:38:29Z","type":"stable","version":"v0.4.6"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.5","date":"2024-10-08T21:06:05Z","type":"stable","version":"v0.4.5"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.4","date":"2024-09-05T15:13:13Z","type":"stable","version":"v0.4.4"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.3","date":"2024-07-01T14:00:36Z","type":"stable","version":"v0.4.3"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.2","date":"2024-03-18T13:07:28Z","type":"stable","version":"v0.4.2"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.1","date":"2024-01-31T15:29:14Z","type":"stable","version":"v0.4.1"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.4.0","date":"2023-12-04T15:08:53Z","type":"stable","version":"v0.4.0"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.3.0","date":"2022-12-08T08:34:37Z","type":"stable","version":"v0.3.0"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.2.0","date":"2022-03-07T02:12:23Z","type":"stable","version":"v0.2.0"},{"url":"https://github.com/EleutherAI/lm-evaluation-harness/releases/tag/v0.0.1","date":"2021-09-02T02:28:08Z","type":"stable","version":"v0.0.1"}]` | `[{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.4.3","date":"2026-01-13T17:47:29Z","type":"stable","version":"v0.4.3"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.4.2","date":"2025-12-23T17:13:41Z","type":"stable","version":"v0.4.2"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.4.1","date":"2025-12-10T16:28:51Z","type":"stable","version":"v0.4.1"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.4.0","date":"2025-12-03T16:22:29Z","type":"stable","version":"v0.4.0"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.9","date":"2025-11-11T17:24:46Z","type":"stable","version":"v0.3.9"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.8","date":"2025-10-28T19:09:17Z","type":"stable","version":"v0.3.8"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.7","date":"2025-10-14T16:21:37Z","type":"stable","version":"v0.3.7"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.6","date":"2025-10-03T03:56:31Z","type":"stable","version":"v0.3.6"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.5","date":"2025-09-17T19:13:15Z","type":"stable","version":"v0.3.5"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.5rc2","date":"2025-09-17T17:40:25Z","type":"prerelease","version":"v0.3.5rc2"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.5rc1","date":"2025-09-17T17:31:23Z","type":"prerelease","version":"v0.3.5rc1"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.4","date":"2025-09-10T23:57:28Z","type":"stable","version":"v0.3.4"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.3","date":"2025-09-04T17:59:51Z","type":"stable","version":"v0.3.3"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.3rc1","date":"2025-09-04T17:46:09Z","type":"prerelease","version":"v0.3.3rc1"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.2","date":"2025-08-19T12:03:50Z","type":"stable","version":"v0.3.2"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.2rc3","date":"2025-08-19T12:01:12Z","type":"prerelease","version":"v0.3.2rc3"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.2-rc2","date":"2025-08-19T11:49:23Z","type":"prerelease","version":"v0.3.2-rc2"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.2-rc1","date":"2025-08-19T10:28:33Z","type":"prerelease","version":"v0.3.2-rc1"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.1","date":"2025-08-11T11:15:03Z","type":"stable","version":"v0.3.1"},{"url":"https://github.com/vibrantlabsai/ragas/releases/tag/v0.3.0","date":"2025-07-17T05:32:24Z","type":"stable","version":"v0.3.0"}]` |
| security.scorecard | 5.5 | - |
| security.trust_center | https://github.com/security | - |
| security.vulnerabilities | `{"count":0,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=lm-eval&per_page=100","last_12m":0,"max_severity":null}` | `{"count":2,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=ragas&per_page=100","last_12m":2,"max_severity":"HIGH"}` |

## Capabilities (AI Evals Testing)

| Capability | LM Evaluation Harness | Ragas |
|---|:--:|:--:|
| **Capabilities** |  |  |
| Architecture model | Open source CLI | Open source CLI |
| LLM as a judge prompt grading framework | - | ✓ |
| Specialized rag metrics faithfulness context relevance | - | - |
| Deterministic regex and json schema assertions | - | - |
| Synthetic test dataset generation from documents | - | ✓ |
| Ci cd github actions pipeline blocking gates | - | - |
| Red teaming and adversarial vulnerability scanning | - | - |
| Multi model side by side ab regression testing | ✓ | - |
| Human in the loop hitl annotation UI | - | - |
| Dashboard analytics for metric drift over time | - | - |
| SOC2 type ii | - | - |
| Mit or apache permissive oss license | - | - |
| Pricing model | Free open source | Free open source |

*Source: vioscaleAI. Generated 2026-10-16T20:15:00.672Z. "-" = undocumented, not absent.*