Open-Source AI · Fine-tuning

PEFT vs Llama Cookbook

PEFT vs Llama Cookbook compared for 2026 — features, license, ease of use, performance and which one to choose. LoRA and friends from Hugging Face vs Official recipes to fine-tune Llama.

Updated regularly · curated by OpenSourceAI.tech

Choose PEFT for cheap fine-tuning with LoRA/QLoRA. Choose Llama Cookbook for fine-tuning Llama models the supported way.

PEFT vs Llama Cookbook at a glance

Spec	PEFT	Llama Cookbook
Category	Fine-tuning	Fine-tuning
Type	Parameter-efficient fine-tuning	Recipes & scripts
License	Apache-2.0	MIT
Runs locally	Yes	Yes
Primary language	Python	Python
Ease of use	Intermediate	Intermediate
Best for	cheap fine-tuning with LoRA/QLoRA	fine-tuning Llama models the supported way
GitHub stars	21.4k	18.4k

How PEFT and Llama Cookbook score

🤝 Too close to call — PEFT and Llama Cookbook land within a hair (4.4 vs 4.3 / 5). Pick on fit, not on score.

Criterion	PEFT	Llama Cookbook
Popularity	3.5	3.5
Maintenance	5.0	4.5
Ease of use	3.5	3.5
Privacy	5.0	5.0
License freedom	5.0	5.0

Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.

What each one is

PEFT

Parameter-efficient fine-tuning · Apache-2.0

PEFT is Hugging Face's library for parameter-efficient fine-tuning, implementing LoRA, QLoRA, adapters and more so you can adapt large models cheaply.

Implements LoRA, QLoRA and adapters
Tight Transformers integration
Train big models on small hardware

See the PEFT page →

Llama Cookbook

Recipes & scripts · MIT

The official Meta cookbook of scripts and notebooks for fine-tuning, evaluating and deploying Llama models.

Official, maintained recipes
Covers fine-tuning to deployment
Well-documented notebooks

See the Llama Cookbook page →

Key differences

PEFT is parameter-efficient fine-tuning, while Llama Cookbook is recipes & scripts. Their licenses differ (Apache-2.0 vs MIT), which matters if you ship a commercial product. In short, PEFT fits cheap fine-tuning with LoRA/QLoRA, and Llama Cookbook fits fine-tuning Llama models the supported way.

Which should you choose?

Choose PEFT for cheap fine-tuning with LoRA/QLoRA. Choose Llama Cookbook for fine-tuning Llama models the supported way.

There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.

Frequently asked questions

Is PEFT or Llama Cookbook easier to use?

Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.

Are PEFT and Llama Cookbook free?

PEFT is free and open source (Apache-2.0), and Llama Cookbook is free and open source (MIT). Neither charges for the core software.

Can I run PEFT and Llama Cookbook locally?

PEFT: yes · Llama Cookbook: yes. Both can be used without sending your data to a third-party cloud where their setup allows.

PEFT vs Llama Cookbook — which should I pick in 2026?

Choose PEFT for cheap fine-tuning with LoRA/QLoRA. Choose Llama Cookbook for fine-tuning Llama models the supported way.

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