# LMDeploy vs MLC LLM

**Leader by vioscaleAI score:** LMDeploy

| Attribute | LMDeploy | MLC LLM |
|---|---|---|
| **vioscaleAI score** | 55.9 (64% (medium)) | 45.4 (39% (low)) |
| activity.commits_last_30d | 66 | 14 |
| adoption.dependent_repos | 2 | 0 |
| adoption.github_stars | 8,104 | 23,247 |
| content.faq | `[{"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}]` | `[{"answer":"An open-source machine learning compiler that enables developers to deploy and optimize large language models efficiently with a unified, OpenAI-compatible API. It is indexed under Model Serving.","source":"https://llm.mlc.ai","question":"What is MLC LLM?","confidence":0.6},{"answer":"MLC LLM 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://llm.mlc.ai","question":"Is MLC LLM free to use?","confidence":0.6},{"answer":"MLC LLM supports the web, Windows, macOS, Linux, iOS, Android and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://llm.mlc.ai","question":"What platforms does MLC LLM support?","confidence":0.6},{"answer":"Yes. MLC LLM can be deployed self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://llm.mlc.ai","question":"Can MLC LLM be self-hosted?","confidence":0.6},{"answer":"Yes. MLC LLM 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/mlc-ai/mlc-llm","question":"Is MLC LLM open source?","confidence":0.95}]` |
| deployment.options | `{"self_hosted":true}` | `{"self_hosted":true}` |
| description.long | LMDeploy is a comprehensive toolkit enabling efficient compression, deployment, and serving of large language models across multiple machines and GPUs with advanced optimization techniques. | A compiler and inference engine that allows developers to build, optimize, and deploy large language models natively on various platforms including mobile devices, web browsers, and servers with GPU acceleration. |
| features.capabilities | `{"gpu_acceleration":true,"continuous_batching":true,"multi_model_serving":true,"multi_gpu_multi_node":true,"quantization_support":true}` | `{"open_source":true,"gpu_acceleration":true,"openai_compatible_api":true}` |
| integrations.count | 2 | - |
| integrations.list | `[{"name":"llm-compressor"},{"name":"OpenCompass"}]` | - |
| language.primary | Python | Python |
| license.spdx | Apache-2.0 | Apache-2.0 |
| platform.support | `{"cli":true,"windows":true}` | `{"ios":true,"mac":true,"web":true,"linux":true,"android":true,"windows":true}` |
| pricing | `{"type":"open_source","freeTier":true,"sourceUrl":"https://lmdeploy.readthedocs.io/en/latest/","retrievedAt":"2026-08-20T12:17:08.568Z"}` | `{"type":"open_source","sourceUrl":"https://llm.mlc.ai","retrievedAt":"2026-08-21T11:07:44.050Z"}` |
| pricing.free_tier | yes | - |
| pricing.model | open_source | open_source |
| pricing.price_level | free | free |
| release.cadence_days | 21 | - |
| release.history | `[{"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"}]` | `[{"url":"https://github.com/mlc-ai/mlc-llm/releases/tag/v0.1.dev0","date":"2023-04-29T03:31:41Z","type":"prerelease","version":"v0.1.dev0"}]` |
| security.vulnerabilities | `{"count":10,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=lmdeploy&per_page=100","last_12m":8,"max_severity":"CRITICAL"}` | `{"count":0,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=spack&package_name=mlc-llm&per_page=100","last_12m":0,"max_severity":null}` |

## Capabilities (Model Serving)

| Capability | LMDeploy | MLC LLM |
|---|:--:|:--:|
| **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 2026-10-16T20:51:11.014Z. "-" = undocumented, not absent.*