Best Model Serving & Inference Platforms Tools

Explore leading tools in the Model Serving & Inference Platforms category, including open-source options and SaaS products. Compare features, use cases, and find the best fit for your workflow.

10+ open-source projects · 5 SaaS products

Top open-source Model Serving & Inference Platforms

These projects are active, self-hostable choices for knowledge management teams evaluating alternatives to SaaS tools.

View all 10+ open-source options
SGLang logo

SGLang

High‑performance serving framework for LLMs and vision‑language models.

Stars
22,604
License
Apache-2.0
Last commit
1 day ago
PythonActive
Most starred project
67,933★

Fast, scalable LLM inference and serving for any workload

Recently updated
1 day ago

High‑throughput LLM serving with PagedAttention, quantization, and multi‑hardware support, offering an OpenAI‑compatible API and seamless Hugging Face integration.

Dominant language
Python • 10+ projects

Expect a strong Python presence among maintained projects.

Popular SaaS Platforms to Replace

Understand the commercial incumbents teams migrate from and how many open-source alternatives exist for each product.

Amazon SageMaker logo

Amazon SageMaker

Fully managed machine learning service to build, train, and deploy ML models at scale

Model Serving & Inference Platforms
Alternatives tracked
15 alternatives
Anyscale logo

Anyscale

Ray-powered platform for scalable LLM training and inference.

Model Serving & Inference PlatformsModel Training & Fine-Tuning Platforms
Alternatives tracked
15 alternatives
BentoML logo

BentoML

Open-source model serving framework to ship AI applications.

Model Serving & Inference Platforms
Alternatives tracked
15 alternatives
Fireworks AI logo

Fireworks AI

High-performance inference and fine-tuning platform for open and proprietary models.

Model Serving & Inference PlatformsModel Training & Fine-Tuning Platforms
Alternatives tracked
15 alternatives
Modal Inference logo

Modal Inference

Serverless GPU inference for AI workloads without managing infra.

Model Serving & Inference Platforms
Alternatives tracked
15 alternatives
Most compared product
10+ open-source alternatives

Amazon SageMaker is a fully managed machine learning service that enables developers and data scientists to build, train, and deploy ML models at scale. It provides a suite of tools including hosted Jupyter notebooks, automated model tuning, one-click training on managed infrastructure, and endpoints for real-time deployment, streamlining the entire ML workflow from data preparation to production model hosting.

Leading hosted platforms

Frequently replaced when teams want private deployments and lower TCO.

Explore related categories

Discover adjacent niches within Model Serving & Inference Platforms.