Model library / NovelAI
Clio is a 3 billion-parameter stablelm model released by NovelAI for fast text generation.
Parameters in total
Context length in tokens, as published
Weights at the released precision
Licence declared on the repository
Overview
Clio is a stablelm-type causal language model trained from scratch by NovelAI on their custom Nerdstash dataset using the Nerdstash Tokenizer V1. The publisher describes it as a fast, original model intended for general text generation, historically competitive with larger models before newer releases.
In practice the model uses 3 billion parameters, supports an 8,192-token context window, and is provided in bfloat16 weight format. It is distributed under the GPL-2.0 licence and can be loaded with the StableLmForCausalLM class without custom code, with GGUF files also available.
Specification
| Repository | NovelAI/clio-v1-legacy |
| Publisher | NovelAI |
| Published | 24 September 2026 |
| Architecture | StableLmForCausalLM |
| Model type | stablelm |
| Parameters | 3,043,786,240 |
| Layers | 28 |
| Hidden size | 2,816 |
| Attention heads | 22, 22 key/value heads |
| Context length | 8,192 tokens |
| Vocabulary | 65,536 tokens |
| Weight format | bfloat16 |
| Licence | gpl-2.0 |
Memory
Parameter count multiplied by the bytes each format uses. The key-value cache comes on top.
| Precision | Weights | Notes |
|---|---|---|
| bf16 | 5.7 GiB | Full precision as released |
| fp8 | 2.8 GiB | 8-bit, near-lossless on most models |
| int4 | 1.4 GiB | 4-bit, smallest footprint |
The cache costs 308 KiB per token at 16-bit, so the full 8,192-token context of one request needs about 2.4 GiB. Concurrency multiplies that number, not the weights.
Hardware
At the released precision, with 90% of the card given to the server and 2.5 GiB kept for the runtime. The context column is what is left for the cache on that setup.
| GPU | Cards needed | Free for cache | Context it holds |
|---|---|---|---|
| RTX 4090 24GB | 1 | 13.4 GiB | the full 8,192 tokens |
| RTX 5090 32GB | 1 | 20.6 GiB | the full 8,192 tokens |
| L40S 48GB | 1 | 35.0 GiB | the full 8,192 tokens |
| A100 80GB | 1 | 63.8 GiB | the full 8,192 tokens |
| H100 80GB | 1 | 63.8 GiB | the full 8,192 tokens |
| RTX PRO 6000 96GB | 1 | 78.2 GiB | the full 8,192 tokens |
| H200 141GB | 1 | 118.7 GiB | the full 8,192 tokens |
Serving
A vLLM launch line for the shape above. Check the model card for a runtime the publisher recommends.
vllm serve NovelAI/clio-v1-legacy \ --max-model-len 8192 \ --gpu-memory-utilization 0.90
Questions
The weights take about 6 GiB at the released precision. That fits on one RTX 4090 24GB, which leaves roughly 13 GiB for the key-value cache.
The repository declares gpl-2.0. Read the licence text before commercial use: the name alone does not tell you what is allowed.
The configuration allows 8,192 tokens. Whether the whole window is usable depends on the memory left for the cache, which the hardware table works out per card.
This page is a reference, and Aiqre does not serve this model today. We deploy open-weight models on dedicated EU hardware on request, so if you want an OpenAI-compatible endpoint for it, email hello@aiqre.com with the model name and roughly what volume you expect.
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Hosting
Tell us the model and roughly what volume you expect. We reply with a price and an OpenAI-compatible endpoint, with your prompts never stored.