# KServe vs LMDeploy

**Leader by vioscaleAI score:** KServe

| Attribute | KServe | LMDeploy |
|---|---|---|
| **vioscaleAI score** | 68.3 (79% (high)) | 55.9 (64% (medium)) |
| activity.commits_last_30d | 100 | 66 |
| adoption.dependent_repos | 178 | 2 |
| adoption.github_stars | 6,115 | 8,104 |
| content.faq | `[{"answer":"A Kubernetes-native platform designed for deploying both generative and predictive AI models, balancing simplicity for quick deployments with enterprise-grade capabilities for large-scale production workloads. It is indexed under Model Serving.","source":"https://kserve.github.io/website/","question":"What is KServe?","confidence":0.6},{"answer":"Yes. KServe can be deployed self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://kserve.github.io/website/","question":"Can KServe be self-hosted?","confidence":0.6},{"answer":"Yes. KServe 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/kserve/kserve","question":"Is KServe 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,"on_prem":true,"self_hosted":true}` | `{"self_hosted":true}` |
| description.long | An open-source platform designed to simplify deployment of machine learning models on Kubernetes while supporting complex enterprise-scale inference with multiple frameworks and advanced optimization features. | 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 | `{"open_source":true,"gpu_acceleration":true,"canary_ab_rollout":true,"kubernetes_native":true,"continuous_batching":true,"multi_model_serving":true,"multi_gpu_multi_node":true,"openai_compatible_api":true,"multi_framework_support":true,"autoscaling_scale_to_zero":true}` | `{"gpu_acceleration":true,"continuous_batching":true,"multi_model_serving":true,"multi_gpu_multi_node":true,"quantization_support":true}` |
| integrations.count | 15 | 2 |
| integrations.list | `[{"name":"Hugging Face","native":true},{"name":"TensorFlow","native":true},{"name":"PyTorch","native":true},{"name":"scikit-learn","native":true},{"name":"XGBoost","native":true},{"name":"ONNX","native":true},{"name":"vLLM","native":true},{"name":"llm-d","native":true},{"name":"Istio","native":true,"category":"service mesh","direction":"bidirectional"},{"name":"Knative Serving","native":true,"category":"serverless","direction":"bidirectional"},{"name":"Envoy","native":true,"category":"networking","direction":"bidirectional"},{"name":"OpenTelemetry","native":true,"category":"observability","direction":"inbound"},{"name":"Prometheus","native":true,"category":"monitoring","direction":"inbound"},{"name":"HuggingFace","native":true},{"name":"MLflow","native":true},{"name":"KEDA","native":true,"category":"autoscaling","direction":"bidirectional"},{"name":"Gateway API","native":true,"category":"networking","direction":"bidirectional"}]` | `[{"name":"llm-compressor"},{"name":"OpenCompass"}]` |
| language.primary | Go | Python |
| license.spdx | Apache-2.0 | Apache-2.0 |
| platform.support | - | `{"cli":true,"windows":true}` |
| pricing | `{"type":"open_source","sourceUrl":"https://kserve.github.io/website/","retrievedAt":"2026-09-14T09:23:10.432Z"}` | `{"type":"open_source","freeTier":true,"sourceUrl":"https://lmdeploy.readthedocs.io/en/latest/","retrievedAt":"2026-08-20T12:17:08.568Z"}` |
| pricing.free_tier | - | yes |
| pricing.model | open_source | open_source |
| pricing.price_level | free | free |
| release.cadence_days | 14 | 21 |
| release.history | `[{"url":"https://github.com/kserve/kserve/releases/tag/v0.21.0","date":"2026-09-25T17:04:20Z","type":"stable","version":"v0.21.0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.21.0-rc1","date":"2026-09-23T01:22:23Z","type":"prerelease","version":"v0.21.0-rc1"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.21.0-rc0","date":"2026-09-10T17:44:50Z","type":"prerelease","version":"v0.21.0-rc0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.20.0","date":"2026-08-06T15:07:42Z","type":"stable","version":"v0.20.0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.20.0-rc1","date":"2026-08-03T23:59:49Z","type":"prerelease","version":"v0.20.0-rc1"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.20.0-rc0","date":"2026-07-16T21:15:07Z","type":"prerelease","version":"v0.20.0-rc0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.18.1","date":"2026-07-15T02:18:38Z","type":"stable","version":"v0.18.1"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.19.0","date":"2026-06-14T03:09:11Z","type":"stable","version":"v0.19.0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.19.0-rc0","date":"2026-05-28T02:19:27Z","type":"prerelease","version":"v0.19.0-rc0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.17.1","date":"2026-05-21T15:30:23Z","type":"stable","version":"v0.17.1"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.18.0","date":"2026-04-29T18:14:59Z","type":"stable","version":"v0.18.0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.18.0-rc1","date":"2026-04-22T16:31:46Z","type":"prerelease","version":"v0.18.0-rc1"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.18.0-rc0","date":"2026-04-20T15:31:27Z","type":"prerelease","version":"v0.18.0-rc0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.17.0","date":"2026-03-13T23:12:37Z","type":"stable","version":"v0.17.0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.17.0-rc1","date":"2026-03-12T14:27:48Z","type":"prerelease","version":"v0.17.0-rc1"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.17.0-rc0","date":"2026-03-06T18:55:36Z","type":"prerelease","version":"v0.17.0-rc0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.16.0","date":"2025-11-03T02:40:28Z","type":"stable","version":"v0.16.0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.16.0-rc1","date":"2025-10-19T19:00:03Z","type":"prerelease","version":"v0.16.0-rc1"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.16.0-rc0","date":"2025-09-15T12:18:38Z","type":"prerelease","version":"v0.16.0-rc0"},{"url":"https://github.com/kserve/kserve/releases/tag/v0.15.2","date":"2025-05-27T07:11:20Z","type":"stable","version":"v0.15.2"}]` | `[{"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.scorecard | 6 | - |
| security.vulnerabilities | `{"count":0,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=kserve&per_page=100","last_12m":0,"max_severity":null}` | `{"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 | KServe | 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 2026-10-17T01:30:52.507Z. "-" = undocumented, not absent.*