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TensorFlow alternatives_

As of 4 November 2026, 39 ml frameworks are named by companies instead of TensorFlow: PyTorch by 5,581 companies, scikit-learn by 1,639, OpenCV by 812.

As of 4 November 2026 · refreshed daily · counts move as websites, DNS and career sites are re-read.

TensorFlow, companies in postings
4,387
Most used alternative
PyTorch · 5,581
Fastest hiring, 90 days
PyTorch
Alternatives ranked
39
Catalogue
T-1.0.1-prov
01 — Ranked by evidence

ml frameworks companies choose instead of TensorFlow

Companies naming each tool in their own postings, and postings in the last 90 days. Bars are relative to the category leader.

#AlternativeCompaniescompaniesvs TensorFlowpostings, 90 dCompare
1
PyTorchPyTorch Foundation
5,581127%17,504TensorFlow vs PyTorch →
2
scikit-learnscikit-learn developers
1,63937%3,810TensorFlow vs scikit-learn →
3
OpenCVOpenCV.org
81219%1,586TensorFlow vs OpenCV →
4
JAXGoogle
74017%1,878TensorFlow vs JAX →
5
61614%1,263TensorFlow vs Hugging Face Transformers →
6
KerasGoogle
60514%1,320TensorFlow vs Keras →
7
57413%1,097TensorFlow vs XGBoost →
8
ONNXLinux Foundation
43510%835TensorFlow vs ONNX →
9
LightGBMMicrosoft
2676%511TensorFlow vs LightGBM →
10
Core MLApple
2145%426TensorFlow vs Core ML →
11
DeepSpeedMicrosoft
2075%328TensorFlow vs DeepSpeed →
12
Hugging Face PEFTHugging Face
2055%508TensorFlow vs Hugging Face PEFT →
13
spaCyExplosion
1934%388TensorFlow vs spaCy →
14
1634%269TensorFlow vs PyTorch FSDP →
15
YOLOUltralytics
1634%281TensorFlow vs YOLO →
16
NLTKNLTK Project
1453%278TensorFlow vs NLTK →
17
1273%513soon
18
1133%284soon
19
1113%579soon
20
SHAPSHAP
1002%215soon
21
Apache TVMApache Software Foundation
942%256soon
22
XLAOpenXLA
792%246soon
23
TRLHugging Face
611%96soon
24
Spark MLlibApache Software Foundation
601%175soon
25
521%142soon
26
LIMELIME
501%110soon
27
CatBoostYandex
471%94soon
28
CaffeBAIR
451%87soon
29
HALCONMVTec
421%113soon
30
verl
401%113soon
31
scikit-imagescikit-image
371%69soon
32
Amazon ComprehendAmazon
341%81soon
33
GensimRARE Technologies
341%54soon
34
FlashAttentionDao-AILab
281%92soon
35
Apache MXNetApache Software Foundation
271%146soon
36
GymnasiumFarama Foundation
271%41soon
37
MediaPipeGoogle
251%24soon
38
IREEOpenXLA
231%53soon
39
MLXApple
231%74soon
18,225 companies name a ml framework in their postings.

Filter on any of them, or on TensorFlow users who also name an alternative, and open the person who owns the stack.

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Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.

39 ml frameworks are named by companies instead of TensorFlow: PyTorch by 5,581 companies, scikit-learn by 1,639, OpenCV by 812, measured from their own job postings. (Breaknorm, 4 November 2026, https://breaknorm.co/tools/tensorflow/alternatives)
How we know

Read from the source, not self-reported

Every number on this page can be traced to a page we crawled or a posting we read. Full methodology →

  • RankingCompanies whose own postings name the tool as the team's system, from the Breaknorm technology catalogue T-1.0.1-prov. Editions are folded into their parent product.
  • 90-day postingsOpen postings first seen or posted in the last 90 days that name the tool.
  • Not includedRatings, prices, feature claims, sponsored positions.
FAQ

TensorFlow alternatives: questions

What is the most used alternative to TensorFlow?

PyTorch: 5,581 companies name it in their own job postings, against 4,387 for TensorFlow.

How is this list ranked?

By the number of companies whose own postings name the tool as the team's system (Breaknorm technology catalogue T-1.0.1-prov), then by postings in the last 90 days. No ratings, no vendor input, no sponsored positions.

Does this say which is better?

No. It says who uses what, by company size, industry and country, so you can see which tools companies like yours choose. For features and prices, read the vendors.

Can I get the companies on any of these?

Yes: click the tool, see the first 20 companies, and sign up for the full list with verified e-mails. Counting is free.

Companies and people

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