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As of 4 November 2026, 39 ml frameworks are named by companies instead of scikit-learn: PyTorch by 5,581 companies, TensorFlow by 4,387, OpenCV by 812.
As of 4 November 2026 · refreshed daily · counts move as websites, DNS and career sites are re-read.
- scikit-learn, companies in postings
- 1,639
- Most used alternative
- PyTorch · 5,581
- Fastest hiring, 90 days
- PyTorch
- Alternatives ranked
- 39
- Catalogue
- T-1.0.1-prov
ml frameworks companies choose instead of scikit-learn
Companies naming each tool in their own postings, and postings in the last 90 days. Bars are relative to the category leader.
| # | Alternative | Companies | companies | vs scikit-learn | postings, 90 d | Compare |
|---|---|---|---|---|---|---|
| 1 | PyTorchPyTorch Foundation | 5,581 | 341% | 17,504 | scikit-learn vs PyTorch → | |
| 2 | TensorFlowGoogle | 4,387 | 268% | 12,007 | scikit-learn vs TensorFlow → | |
| 3 | OpenCVOpenCV.org | 812 | 50% | 1,586 | scikit-learn vs OpenCV → | |
| 4 | JAXGoogle | 740 | 45% | 1,878 | scikit-learn vs JAX → | |
| 5 | Hugging Face TransformersHugging Face | 616 | 38% | 1,263 | scikit-learn vs Hugging Face Transformers → | |
| 6 | KerasGoogle | 605 | 37% | 1,320 | scikit-learn vs Keras → | |
| 7 | XGBoostDMLC | 574 | 35% | 1,097 | scikit-learn vs XGBoost → | |
| 8 | ONNXLinux Foundation | 435 | 27% | 835 | scikit-learn vs ONNX → | |
| 9 | LightGBMMicrosoft | 267 | 16% | 511 | scikit-learn vs LightGBM → | |
| 10 | Core MLApple | 214 | 13% | 426 | scikit-learn vs Core ML → | |
| 11 | DeepSpeedMicrosoft | 207 | 13% | 328 | scikit-learn vs DeepSpeed → | |
| 12 | Hugging Face PEFTHugging Face | 205 | 13% | 508 | scikit-learn vs Hugging Face PEFT → | |
| 13 | spaCyExplosion | 193 | 12% | 388 | scikit-learn vs spaCy → | |
| 14 | PyTorch FSDPMeta | 163 | 10% | 269 | scikit-learn vs PyTorch FSDP → | |
| 15 | YOLOUltralytics | 163 | 10% | 281 | scikit-learn vs YOLO → | |
| 16 | NLTKNLTK Project | 145 | 9% | 278 | scikit-learn vs NLTK → | |
| 17 | TensorFlow LiteGoogle | 127 | 8% | 513 | soon | |
| 18 | Megatron-LMNVIDIA | 113 | 7% | 284 | soon | |
| 19 | NVIDIA NeMoNVIDIA | 111 | 7% | 579 | soon | |
| 20 | SHAPSHAP | 100 | 6% | 215 | soon | |
| 21 | Apache TVMApache Software Foundation | 94 | 6% | 256 | soon | |
| 22 | XLAOpenXLA | 79 | 5% | 246 | soon | |
| 23 | TRLHugging Face | 61 | 4% | 96 | soon | |
| 24 | Spark MLlibApache Software Foundation | 60 | 4% | 175 | soon | |
| 25 | 52 | 3% | 142 | soon | ||
| 26 | LIMELIME | 50 | 3% | 110 | soon | |
| 27 | CatBoostYandex | 47 | 3% | 94 | soon | |
| 28 | CaffeBAIR | 45 | 3% | 87 | soon | |
| 29 | HALCONMVTec | 42 | 3% | 113 | soon | |
| 30 | verl | 40 | 2% | 113 | soon | |
| 31 | scikit-imagescikit-image | 37 | 2% | 69 | soon | |
| 32 | Amazon ComprehendAmazon | 34 | 2% | 81 | soon | |
| 33 | GensimRARE Technologies | 34 | 2% | 54 | soon | |
| 34 | FlashAttentionDao-AILab | 28 | 2% | 92 | soon | |
| 35 | Apache MXNetApache Software Foundation | 27 | 2% | 146 | soon | |
| 36 | GymnasiumFarama Foundation | 27 | 2% | 41 | soon | |
| 37 | MediaPipeGoogle | 25 | 2% | 24 | soon | |
| 38 | IREEOpenXLA | 23 | 1% | 53 | soon | |
| 39 | MLXApple | 23 | 1% | 74 | soon |
Filter on any of them, or on scikit-learn users who also name an alternative, and open the person who owns the stack.
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39 ml frameworks are named by companies instead of scikit-learn: PyTorch by 5,581 companies, TensorFlow by 4,387, OpenCV by 812, measured from their own job postings. (Breaknorm, 4 November 2026, https://breaknorm.co/tools/scikit-learn/alternatives)
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.
scikit-learn alternatives: questions
What is the most used alternative to scikit-learn?
PyTorch: 5,581 companies name it in their own job postings, against 1,639 for scikit-learn.
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.
Get these companies your way
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