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LLM Index

Guanaco vs. Koala

A side-by-side comparison of release history, capabilities, licensing and model sizes.

Attribute Guanaco Koala
Developer UW NLP BAIR
Current generation – –
Initial release 2023-05-23 2023-04-03
Instruct tuned Yes Yes
Coding No No
Finetuning Yes Yes
Open source Yes Yes
License Noncommercial Noncommercial
Model sizes 7B, 13B, 33B, 65B 7B, 13B
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Guanaco

Guanaco is an LLM based off the QLoRA 4-bit finetuning method developed by Tim Dettmers et. al. in the UW NLP group. Guanaco achieves 99% ChatGPT performance on the Vicuna benchmark.

Guanaco is an LLM that uses a finetuning method called LoRA that was developed by Tim Dettmers et. al. in the UW NLP group. With QLoRA, it becomes possible to finetune up to a 65B parameter model on a 48GB GPU without loss of performance relative to a 16-bit model. The Guanaco model family outperforms all previously released models on the Vicuna benchmark. However, given the models are based off of the LLaMA model family, commercial use is not permitted.

Further reading

Koala

Released alongside Vicuna, Koala is one of many descendants of the Meta LLaMA model trained on dialogue data collected from the web. On the developers' benchmarks, Koala outperforms its sibling Alpaca, though its adoption has been significantly less than that of its other sibling, Vicuna. Due to its use of LLaMA, only research use is permitted.

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