Model Serving
Top signal weightsIntegrations 0.16Package downloads 0.14Development activity 0.09Capabilities 0.08
Rank by intent
Ranking basisMost actively maintainedGithub activity 0.17Integrations 0.14Package downloads 0.12Capabilities 0.07
Same facts, re-weighted. Only the weighting changes, never the underlying evidence.
| # | Software | Score | Confidence |
|---|---|---|---|
| 1 | Ollama | 78 | medium · 52% |
| 2 | KServe | 69 | low · 24% |
| 3 | vLLM | 69 | medium · 55% |
| 4 | TorchServe | 63 | low · 34% |
| 5 | BentoML | 53 | low · 41% |
| 6 | NVIDIA NIMSelf-hosted GPU-accelerated inference containers for deploying AI models across clouds and edge devices | 49 | low · 36% |
| 7 | LMDeploy | 49 | low · 30% |
| 8 | NVIDIA Triton Inference Server | 47 | low · 30% |
| 9 | Hugging Face Text Generation Inference | 47 | low · 33% |
| 10 | Amazon SageMaker InferenceA cloud platform for deploying machine learning models with low-latency and high-throughput inference capabilities | 36 | low · 40% |
| 11 | MLC LLM | 27 | low · 23% |
| 12 | SGLangA framework for hosting and running large language models on diverse GPU hardware with efficient inference | 14 | low · 3% |
Ranked by the Vioscale composite: independent signals, not user reviews. See the method.
Model Serving compared
Head-to-head on the attributes that matter here, with a source and date on every value.