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transformers vs unsloth

Gemma rivals. Both tagged gemma, deepseek. Six rounds of real GitHub data, an AI referee, and the crowd picks a side.

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huggingface/transformers: 168,811 stars, Python. 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models,…
unslothai/unsloth: 79,320 stars, Python. Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more.

transformers vs unsloth: tale of the tape

GitHub data as of November 11, 2026

transformers has 2.1 times as many GitHub stars as unsloth (168,811 vs 79,320). In the last 6 days, unsloth gained more stars: +248 (+0.3%) against +243 (+0.1%) for transformers. unsloth saw more development in the last 52 weeks with 16,849 commits, against 4,727 for transformers. transformers is the older project (created October 2018), unsloth started in November 2023. Both are written mainly in Python.

huggingface/transformersunslothai/unsloth
Stars168,81179,320
Stars gained, last 6 days+243+248
Growth, last 6 days+0.1%+0.3%
Avg. stars per day since creation5874
Forks35,1877,385
Commits, last 52 weeks4,72716,849
Open issues1,073474
Best Repocharts rank today#13 in Python#37 in AI
LanguagePythonPython
LicenseApache-2.0Apache-2.0
CreatedOct 29, 2018Nov 29, 2023
Last pushNov 11, 2026Nov 11, 2026

Quick answers

Which is more popular, transformers or unsloth?

transformers has 2.1 times as many GitHub stars as unsloth (168,811 vs 79,320) (Repocharts data as of November 11, 2026).

Which is growing faster, transformers or unsloth?

In the last 6 days, unsloth gained more stars: +248 (+0.3%) against +243 (+0.1%) for transformers.

Which is more actively developed?

unsloth saw more development in the last 52 weeks with 16,849 commits, against 4,727 for transformers.

What languages are transformers and unsloth written in?

Both are written mainly in Python.

How does RepoClash compare transformers and unsloth?

RepoClash scores both repositories in six rounds (popularity, momentum, activity, community, maintenance and freshness) from public GitHub data, adds an AI referee's verdict and lets developers vote for their favorite. Star counts are updated daily.

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