Looking for something like Infer.NET? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 7 are open source.
Infer.NET runs Bayesian inference in graphical models for a range of machine learning problems.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Espresso AI | — | Not stated | Web |
| 2 | Cortex | — | Not stated | Web |
| 3 | Seldon-core | — | Not stated | — |
| 4 | Kubeflow | — | Yes | — |
| 5 | delta | — | Yes | — |
| 6 | Caffe | — | Not stated | Windows |
| 7 | Catniff | — | Yes | — |
| 8 | dfdx | — | Not stated | — |
| 9 | cONNXr | — | Yes | — |
| 10 | PyTorch | — | Not stated | — |
Espresso AI uses machine learning to optimize Snowflake and Databricks data warehouses and reduce query and infrastructure costs.
Cortex provides cloud infrastructure for deploying, managing, and scaling machine learning models in production.
MLOps framework to package, deploy, monitor and manage thousands of production machine learning models.
Kubeflow provides a machine learning toolkit for deploying workflows on Kubernetes.
Build machine learning applications with Delta, an open-source framework implemented in Rust.
Caffe provides an open framework for building and running deep learning models.
Catniff provides JavaScript developers with a Torch-like deep learning framework.
Deep learning in Rust, with shape checked tensors and neural networks.
The cONNXr project provides a pure C runtime for ONNX models intended for embedded devices.
Tensors and Dynamic neural networks in Python with strong GPU acceleration.
Prime Intellect provides compute, training, inference, and sandbox tools for training and deploying machine learning models.
Algorithms for learning and inference with discrete probabilistic models.
Stakpak runs an agent on a machine to ship code and keep applications running.
Groq provides cloud infrastructure and developer APIs for running AI model inference.
Baseten provides an inference platform for serving and scaling open-source and custom AI models in production.
Run sandboxes, task queues, and custom model inference with ultrafast boot times, instant autoscaling, and a developer experience that just works.
Runpod provides on-demand GPUs and serverless compute for AI model training, fine-tuning, inference, and batch workloads.
Apertus provides a nonprofit public inference service intended to make public and sovereign AI models more accessible.
Colibri runs mixture-of-experts language models on local hardware, streaming experts from disk with a small C engine.
Ollama runs language models locally and provides tools to work with model files and APIs.
Hopsworks provides a feature store and MLOps platform for building and operating production machine learning systems.
DigitalOcean offers cloud infrastructure for AI agents, inference, and production AI products.
CoreWeave presents cloud infrastructure for AI and machine learning, with deployment and scaling for production models.
ClearML provides AI infrastructure for managing GPU clusters, machine learning workflows, and model deployment.
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
