Model reference · open weights

clio-legacy

LLMs NovelAI Text gen 1 build Open, with conditions 2k dl/mo

clio-legacy is an open-weight language model from NovelAI. clio-v1-legacy (BF16) weighs 2.0 GB; the smallest configuration that runs it is RTX 3060 12 GB.

For self-hosting, compare this build's requirements below with the GPU you plan to rent.

  • Clio is a 3.0 billion parameter text-generation model developed by NovelAI and released as clio-v1-legacy.
  • It supports English with a context length of 8192 tokens and is distributed under the GPL-2.0 license.
  • The model was pretrained from scratch on a custom dataset and is provided with GGUF format files for use.

Summary of the NovelAI/clio-v1-legacy model card, 2026-10-01

What it is

Released byNovelAI
Released2026-09-24
Parameters3.0B
VRAM2.0 GB for the weights

What it runs on

Memory and cards for clio-v1-legacy (BF16)

2.0 GBweights, file size
315 MBcache per 1K tokens
495 MBruntime overhead, at least
8,192 tokenscontext max
CardRequests at onceContext maxMemory
8K each
RTX 3060 12 GB3all 8K11.6 GB
RTX 4060 Ti 16 GB5all 8K15.4 GB
RTX 3090 24 GB8all 8K23.4 GB
RTX 4090 24 GB8all 8K23.4 GB
RTX 5090 32 GB11all 8K31.0 GB
L40S 48 GB16all 8K44.0 GB
A100 80 GB29all 8K78.2 GB
H100 80 GB29all 8K78.1 GB
RTX PRO 6000 Blackwell 96 GB35all 8K93.8 GB
DGX Spark (GB10) 128 GB unified40all 8K107 GB
H200 141 GB52all 8K138 GB
B200 180 GB67all 8K176 GB
2× RTX 3060 12 GB
split by layers (llama.cpp)
7all 8K11.6 GB a card
2× RTX 4060 Ti 16 GB
split by layers (llama.cpp)
10all 8K15.4 GB a card
Memory needed at each load
Requests at once8K tokens each
15.1 GB
515.4 GB
823.1 GB
1643.8 GB
3285.1 GB
64168 GB

One card, with vLLM's small-card settings.

From the model card

What NovelAI says about clio-legacy

Read the model card

Clio is the first fully original large language model that we pretrained from scratch on our Shoggy H100 cluster. At 3 billion paramters, she runs very fast, but thanks to the, for her time, very large training volume, her writing outperforms much bigger models like Euterpe and Krake. She was trained on our custom Nerdstash dataset, with our custom Nerdstash Tokenizer V1.

Back when she was released, Clio was very competitive across various evaluation metrics, even when compared with much bigger models. The following table shows the performance of the base model before being finetuned for story telling:

Nowadays, much stronger models, like Kayra, Erato and Xialong are available on NovelAI, so before long, Clio will get to enjoy a peaceful retirement.

So, in anticipation of this, for the sake of nostalgia, posterity, and historic preservation, we are releasing the weights of our Clio model and her modules publicly on Huggingface Hub under the GPL-2.0 (not "or later") license.

We managed to find an existing model class inside Huggingface Transformers which fits the shape of our architecture for Clio, at least once an additional config flag is set, so no custom code is needed to run Clio. Model files in GGUF format are provided as well.

You can find your very own Clio right here where you are!

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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