mradermacher/mox-small-1-GGUF

---

base_model: vanta-research/mox-small-1 language:

• en

library_name: transformers license: apache-2.0 mradermacher: readme_rev: 1 quantized_by: mradermacher tags:

• vanta-research
• alignment
• text-generation-inference
• cognitive-fit
• persona-research
• conversational-ai
• conversational
• large-language-model
• chat
• chatbot
• olmo3.1
• allenai
• ai2
• finetune
• ai-research
• ai-alignment-research
• ai-persona-research
• personality-ai
• ai-alignment
• ai-behavior
• ai-behavior-research
• human-ai-collaboration

---

About

static quants of https://huggingface.co/vanta-research/mox-small-1

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/mox-small-1-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's
READMEs for
more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link	Type	Size/GB	Notes
GGUF	Q2_K	12.1
GGUF	Q3K_S	14.2
GGUF	Q3K_M	15.7	lower quality
GGUF	Q3K_L	17.0
GGUF	IQ4_XS	17.6
GGUF	Q4K_S	18.5	fast, recommended
GGUF	Q4K_M	19.6	fast, recommended
GGUF	Q5K_S	22.3
GGUF	Q5K_M	23.0
GGUF	Q6_K	26.5	very good quality
GGUF	Q8_0	34.4	fast, best quality

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

!image.png

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.