# BentoML vs LMDeploy

| Attribute | BentoML | LMDeploy |
|---|---|---|
| **vioscaleAI score** | 52.4 (43% (low)) | 55.9 (64% (medium)) |
| activity.commits_last_30d | 6 | 66 |
| adoption.dependent_repos | 499 | 2 |
| adoption.github_stars | 8,900 | 8,104 |
| content.faq | `[{"answer":"An open-source framework for packaging, deploying, and managing AI model inference at scale, supporting any model architecture or framework with options for cloud or on-premises deployment. It is indexed under MLOps & LLMOps Tools.","source":"https://www.bentoml.com","question":"What is BentoML?","confidence":0.6},{"answer":"BentoML offers a free tier, so you can start without paying. Pricing changes often, so verify at source before relying on it.","source":"https://www.bentoml.com","question":"Is BentoML free?","confidence":0.6},{"answer":"Yes. BentoML can be deployed cloud / SaaS, hybrid, on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://www.bentoml.com","question":"Can BentoML be self-hosted?","confidence":0.6},{"answer":"Yes. BentoML 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/bentoml/bentoml","question":"Is BentoML open source?","confidence":0.95}]` | `[{"answer":"A software framework that enables developers to compress, deploy, and serve large language models with quantization optimization, multiple inference engines, and compatibility across various model architectures. It is indexed under Model Serving.","source":"https://lmdeploy.readthedocs.io/en/latest/","question":"What is LMDeploy?","confidence":0.6},{"answer":"LMDeploy 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://lmdeploy.readthedocs.io/en/latest/","question":"Is LMDeploy free to use?","confidence":0.6},{"answer":"LMDeploy supports Windows and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://lmdeploy.readthedocs.io/en/latest/","question":"What platforms does LMDeploy support?","confidence":0.6},{"answer":"Yes. LMDeploy can be deployed self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://lmdeploy.readthedocs.io/en/latest/","question":"Can LMDeploy be self-hosted?","confidence":0.6},{"answer":"Yes. LMDeploy 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/internlm/lmdeploy","question":"Is LMDeploy open source?","confidence":0.95}]` |
| deployment.options | `{"cloud":true,"hybrid":true,"self_hosted":true}` | `{"self_hosted":true}` |
| description.long | A Python library that enables developers to create REST API services for AI model inference with features like dynamic batching, multi-model orchestration, and containerized deployment. | LMDeploy is a comprehensive toolkit enabling efficient compression, deployment, and serving of large language models across multiple machines and GPUs with advanced optimization techniques. |
| features.capabilities | `{"role":"platform","open_source":true,"managed_cloud":true,"model_serving":true,"self_hostable":true,"multi_provider":true,"vpc_deployment":true,"dynamic_batching":true,"gpu_acceleration":true,"kubernetes_native":true,"llm_observability":true,"framework_agnostic":true,"continuous_batching":true,"multi_model_serving":true,"multi_gpu_multi_node":true,"openai_compatible_api":true,"multi_framework_support":true}` | `{"gpu_acceleration":true,"continuous_batching":true,"multi_model_serving":true,"multi_gpu_multi_node":true,"quantization_support":true}` |
| integrations.count | 1 | 2 |
| integrations.list | `[{"name":"Datadog","category":"observability"}]` | `[{"name":"llm-compressor"},{"name":"OpenCompass"}]` |
| language.primary | Python | Python |
| license.spdx | Apache-2.0 | Apache-2.0 |
| platform.support | `{"cli":true,"web":true}` | `{"cli":true,"windows":true}` |
| pricing | `{"type":"hybrid","freeTier":true,"sourceUrl":"https://www.bentoml.com","retrievedAt":"2026-08-21T13:19:12.207Z"}` | `{"type":"open_source","freeTier":true,"sourceUrl":"https://lmdeploy.readthedocs.io/en/latest/","retrievedAt":"2026-08-20T12:17:08.568Z"}` |
| pricing.free_tier | yes | yes |
| pricing.model | commercial | open_source |
| pricing.price_level | low | free |
| release.cadence_days | 12 | 21 |
| release.history | `[{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.39","date":"2026-05-07T10:37:29Z","type":"stable","version":"v1.4.39"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.38","date":"2026-04-02T06:12:17Z","type":"stable","version":"v1.4.38"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.37","date":"2026-03-25T01:20:40Z","type":"stable","version":"v1.4.37"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.36","date":"2026-03-06T04:25:28Z","type":"stable","version":"v1.4.36"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.35","date":"2026-02-03T05:06:31Z","type":"stable","version":"v1.4.35"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.34","date":"2026-01-26T03:19:56Z","type":"stable","version":"v1.4.34"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.33","date":"2026-01-12T10:26:47Z","type":"stable","version":"v1.4.33"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.32","date":"2026-01-09T02:22:49Z","type":"stable","version":"v1.4.32"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.31","date":"2025-12-23T06:51:00Z","type":"stable","version":"v1.4.31"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.30","date":"2025-11-27T03:15:11Z","type":"stable","version":"v1.4.30"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.29","date":"2025-11-17T12:02:22Z","type":"stable","version":"v1.4.29"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.28","date":"2025-10-29T06:09:36Z","type":"stable","version":"v1.4.28"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.27","date":"2025-10-20T06:57:33Z","type":"stable","version":"v1.4.27"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.26","date":"2025-10-10T07:28:39Z","type":"stable","version":"v1.4.26"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.25","date":"2025-09-24T08:51:56Z","type":"stable","version":"v1.4.25"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.24","date":"2025-09-17T09:30:34Z","type":"stable","version":"v1.4.24"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.23","date":"2025-09-05T00:51:38Z","type":"stable","version":"v1.4.23"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.22","date":"2025-08-27T01:20:34Z","type":"stable","version":"v1.4.22"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.21","date":"2025-08-14T01:07:36Z","type":"stable","version":"v1.4.21"},{"url":"https://github.com/bentoml/BentoML/releases/tag/v1.4.20","date":"2025-08-13T08:02:48Z","type":"stable","version":"v1.4.20"}]` | `[{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.18.0","date":"2026-09-28T07:04:58Z","type":"stable","version":"v0.18.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.17.0","date":"2026-09-01T07:13:39Z","type":"stable","version":"v0.17.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.16.0","date":"2026-08-19T04:43:53Z","type":"stable","version":"v0.16.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.15.0","date":"2026-07-31T13:00:46Z","type":"stable","version":"v0.15.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.14.0","date":"2026-06-24T04:36:56Z","type":"stable","version":"v0.14.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/0.14.0a2","date":"2026-06-16T04:16:04Z","type":"prerelease","version":"0.14.0a2"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/0.14.0a1","date":"2026-06-01T08:46:02Z","type":"prerelease","version":"0.14.0a1"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.13.0","date":"2026-05-12T03:46:57Z","type":"stable","version":"v0.13.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.12.3","date":"2026-04-08T03:37:26Z","type":"stable","version":"v0.12.3"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.12.2","date":"2026-03-18T03:13:55Z","type":"stable","version":"v0.12.2"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.12.1","date":"2026-02-13T09:02:12Z","type":"stable","version":"v0.12.1"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.12.0","date":"2026-02-04T06:28:25Z","type":"stable","version":"v0.12.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.11.1","date":"2025-12-24T13:27:06Z","type":"stable","version":"v0.11.1"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.11.0","date":"2025-12-04T06:20:38Z","type":"stable","version":"v0.11.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.10.2","date":"2025-10-28T11:32:42Z","type":"stable","version":"v0.10.2"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.10.1","date":"2025-09-26T02:45:30Z","type":"stable","version":"v0.10.1"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.10.0","date":"2025-09-09T05:05:09Z","type":"stable","version":"v0.10.0"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.9.2.post1","date":"2025-08-19T09:44:41Z","type":"stable","version":"v0.9.2.post1"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.9.2","date":"2025-07-26T10:00:25Z","type":"stable","version":"v0.9.2"},{"url":"https://github.com/InternLM/lmdeploy/releases/tag/v0.9.1","date":"2025-07-04T10:05:31Z","type":"stable","version":"v0.9.1"}]` |
| reliability.status_page | yes | - |
| security.scorecard | 7 | - |
| security.vulnerabilities | `{"count":16,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=bentoml&per_page=100","last_12m":8,"max_severity":"CRITICAL"}` | `{"count":10,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=lmdeploy&per_page=100","last_12m":8,"max_severity":"CRITICAL"}` |

## Capabilities (Model Serving)

| Capability | BentoML | LMDeploy |
|---|:--:|:--:|
| **Capabilities** |  |  |
| Continuous batching | ✓ | ✓ |
| Dynamic batching | ✓ | - |
| Multi framework support | ✓ | - |
| GPU acceleration | ✓ | ✓ |
| Multi GPU multi node | ✓ | ✓ |
| Quantization support | - | ✓ |
| Openai compatible API | ✓ | - |
| Autoscaling scale to zero | - | - |
| Multi model serving | ✓ | ✓ |
| Canary ab rollout | - | - |
| Kubernetes native | ✓ | - |
| Open source | ✓ | - |

*Source: vioscaleAI. Generated 2026-10-17T05:43:32.074Z. "-" = undocumented, not absent.*