1
dfdx
github.com/coreylowman/dfdxAlso covers ai infrastructure, computing, and machine learning · same kind of open-source project
Deep learning in Rust, with shape checked tensors and neural networks.
Alternatives
The Best burn Alternatives in 2026
24 alternatives0 free · 22 open source
Looking for something like burn? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 22 are open source.
Burn provides a flexible, efficient, and portable tensor library for building deep learning applications.
Top picks at a glance
First suggestiondfdxDeep learning in Rust, with shape checked tensors and…Open source optiondstackdstack provides an open framework for confidential AI…
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | dfdx | — | Not stated | — |
| 2 | dstack | — | Yes | — |
| 3 | FlexML | — | Yes | — |
| 4 | TFServing | — | Yes | — |
| 5 | Catniff | — | Yes | — |
| 6 | qkeras | — | Yes | — |
| 7 | deepjavalibrary/djl | — | Yes | Android |
| 8 | PaddlePaddle | — | Yes | — |
| 9 | MegEngine | — | Yes | — |
| 10 | Oneflow | — | Yes | — |
All burn alternatives
2
Also covers ai infrastructure, computing, and open source · same kind of open-source project
dstack provides an open framework for confidential AI computing and deployments.
3
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
FlexML offers an easy to use and flexible automated machine learning library for Python.
4
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Flexible, high-performance serving system for machine learning models.
5
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Catniff provides JavaScript developers with a Torch-like deep learning framework.
6
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
QKeras provides quantization tools for deep learning with TensorFlow Keras.
7
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
DJL is a Java framework for running deep learning models across different engines.
8
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
PaddlePaddle provides a deep learning framework for training models across devices and platforms.
9
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
The MegEngine framework supports deep learning and automatic differentiation, according to its repository description.
10
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Train and run models with OneFlow, a scalable deep learning framework for distributed machine learning workloads.
11
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Build neural networks and support machine learning research with Sonnet, a library based on TensorFlow.
12
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Build machine learning applications with Delta, an open-source framework implemented in Rust.
13
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Use Aeromancy to build reproducible machine learning workflows and projects.
14
Awesome Tensor Compilers
github.com/merrymercy/awesome-tensor-compilersAlso covers ai infrastructure and machine learning · same kind of open-source project
List of awesome compiler projects and papers for tensor computation and deep learning.
15
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
BentoML helps build and serve AI apps and models through inference APIs, job queues, and multi-model pipelines.
16
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
FLAML provides a fast Python library for automated machine learning and tuning.
17
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
The fuku-ml project provides a machine learning library described as simple to use.
18
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
The goro project provides a high level machine learning library written for Go.
19
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Kubeflow Pipelines orchestrates and manages machine learning workflows on Kubeflow.
20
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Sagify describes its project as a way to work with large language models and machine learning more easily.
21
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
TPOT uses genetic programming to optimize machine learning pipelines in Python.
22
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
ORMB packages machine learning models as OCI artifacts, in a workflow described as Docker for ML models.
23
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Merlin supports machine learning model management, deployment, and serving in Kubernetes environments.
24
Also covers ai infrastructure, machine learning, and open source · same kind of open-source project
Cog packages machine learning models into containers to support deployment across environments.
No alternatives match this filter.
Alternatives to similar tools
Kubeflow Pipelines24 alternativesFlexML24 alternativesCatniff24 alternativesqkeras24 alternativesAwesome Tensor Compilers24 alternativesMerlin24 alternatives
What is the best alternative to burn?
Based on features, tags and platforms, the closest alternatives to burn are dfdx, dstack, and FlexML.
Are there open-source alternatives to burn?
Yes: dstack, FlexML, TFServing, and Catniff.
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