Model Serving
Top signal weightsIntegrations 0.16Package downloads 0.14Development activity 0.09Capabilities 0.08
Rank by intent
Balanced is the citeable default. The facts never change, only how the signals are weighted.
| # | Software | Score | Confidence |
|---|---|---|---|
| 1 | Ollama | 79 | low · 49%updating |
| 2 | KServe | 70 | low · 19%updating |
| 3 | vLLM | 69 | medium · 51%updating |
| 4 | TorchServe | 63 | low · 28%updating |
| 5 | BentoML | 57 | low · 38%updating |
| 6 | Hugging Face Text Generation Inference | 54 | low · 27%updating |
| 7 | NVIDIA NIMSelf-hosted GPU-accelerated inference containers for deploying AI models across clouds and edge devices | 49 | low · 36%updating |
| 8 | NVIDIA Triton Inference Server | 48 | low · 24%updating |
| 9 | LMDeploy | 44 | low · 23%updating |
| 10 | Amazon SageMaker InferenceA cloud platform for deploying machine learning models with low-latency and high-throughput inference capabilities | 36 | low · 40%updating |
| 11 | MLC LLM | 31 | low · 19%updating |
| 12 | SGLangA framework for hosting and running large language models on diverse GPU hardware with efficient inference | 14 | low · 3%updating |
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.