# LMDeploy vs NVIDIA NIM

**Leader by vioscaleAI score:** LMDeploy

| Attribute | LMDeploy | NVIDIA NIM |
|---|---|---|
| **vioscaleAI score** | 55.9 (64% (medium)) | 49.2 (74% (medium)) |
| activity.commits_last_30d | 66 | - |
| adoption.dependent_repos | 2 | - |
| adoption.github_stars | 8,104 | - |
| 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":"A containerized microservices platform for running AI models on NVIDIA GPUs with industry-standard APIs. Supports deployment across clouds, data centers, and edge devices, with built-in optimization for inference performance and throughput. It is indexed under Model Serving.","source":"https://developer.nvidia.com/nim","question":"What is NVIDIA NIM?","confidence":0.6},{"answer":"NVIDIA NIM offers a free tier, so you can start without paying. Pricing changes often, so verify at source before relying on it.","source":"https://developer.nvidia.com/nim","question":"Is NVIDIA NIM free?","confidence":0.6},{"answer":"NVIDIA NIM supports Linux and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://developer.nvidia.com/nim","question":"What platforms does NVIDIA NIM support?","confidence":0.6},{"answer":"Yes. NVIDIA NIM can be deployed cloud / SaaS, on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://developer.nvidia.com/nim","question":"Can NVIDIA NIM be self-hosted?","confidence":0.6},{"answer":"We have confirmed 9 integrations for NVIDIA NIM, including LangChain, CrewAI, Agno, LangSmith, Microsoft AutoGen, Google ADK, Hugging Face and Docker, plus 1 more. This is what we could verify from public sources, so the vendor may support others we have not indexed.","source":"https://developer.nvidia.com/nim","question":"What does NVIDIA NIM integrate with?","confidence":0.6}]` |
| deployment.options | `{"self_hosted":true}` | `{"cloud":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. | NVIDIA NIM provides ready-optimized inference containers with standard APIs that enable developers to deploy large language models and AI applications with reduced latency, supporting multiple frameworks and deployment environments from development to production. |
| features.capabilities | `{"gpu_acceleration":true,"continuous_batching":true,"multi_model_serving":true,"multi_gpu_multi_node":true,"quantization_support":true}` | `{"open_source":false,"gpu_acceleration":true,"kubernetes_native":true,"multi_model_serving":true,"multi_gpu_multi_node":true,"multi_framework_support":true}` |
| integrations.count | 2 | 9 |
| integrations.list | `[{"name":"llm-compressor"},{"name":"OpenCompass"}]` | `[{"name":"LangChain"},{"name":"CrewAI"},{"name":"Agno"},{"name":"LangSmith"},{"name":"Microsoft AutoGen"},{"name":"Google ADK"},{"name":"Hugging Face"},{"name":"Docker"},{"name":"Kubernetes"},{"name":"vLLM","native":false,"category":"inference"},{"name":"SGLang","native":false,"category":"inference"},{"name":"TensorRT-LLM","native":false,"category":"inference"}]` |
| language.primary | Python | - |
| license.spdx | Apache-2.0 | - |
| platform.support | `{"cli":true,"windows":true}` | `{"cli":true}` |
| pricing | `{"type":"open_source","freeTier":true,"sourceUrl":"https://lmdeploy.readthedocs.io/en/latest/","retrievedAt":"2026-08-20T12:17:08.568Z"}` | `{"type":"hybrid","summary":"Free tier for development prototyping; paid membership for hosted services","freeTier":true,"sourceUrl":"https://developer.nvidia.com/nim","retrievedAt":"2026-08-21T11:00:58.822Z"}` |
| pricing.free_tier | yes | yes |
| pricing.model | open_source | freemium |
| pricing.price_level | free | low |
| pricing.transparent | - | no |
| 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"}]` | - |
| 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"}` | - |

## Capabilities (Model Serving)

| Capability | LMDeploy | NVIDIA NIM |
|---|:--:|:--:|
| **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 2026-10-16T20:10:36.887Z. "-" = undocumented, not absent.*