base_model: AEON-7/Gemma-4-12B-it-AEON-Abliterated-K4-BF16
language:
- en
library_name: transformers
license: gemma
model_type: gemma4_unified
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags: - 12b
- aarch64
- abliterated
- aeon
- aeon-7
- agentic
- arm64
- bf16
- bfloat16
- biprojection
- blackwell
- capability-preserving
- chat
- chunked-prefill
- coding
- conversational
- dense
- dgx-spark
- english
- function-calling
- gb10
- gemma
- gemma-4
- gemma-4-12B
- gemma4
- gemma4_unified
- gpu
- grace-blackwell
- heretic
- instruct
- k4-biprojection
- long-context
- low-drift
- multi-direction-biprojection
- multimodal
- multimodal-capable
- nvidia
- openai-api
- openai-compatible
- prefix-caching
- production-ready
- reasoning
- refusal-removed
- safetensors
- sm_121a
- text-generation
- thinking
- tool-calling
- transformer
- transformers
- trevor-js
- uncensored
- unfiltered
- vision
- vision-language
- vllm
About
static quants of https://huggingface.co/AEON-7/Gemma-4-12B-it-AEON-Abliterated-K4-BF16
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Gemma-4-12B-it-AEON-Abliterated-K4-BF16-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 | 4.9 | |
| GGUF | Q3_K_S | 5.6 | |
| GGUF | Q3_K_M | 6.2 | lower quality |
| GGUF | Q3_K_L | 6.7 | |
| GGUF | IQ4_XS | 6.8 | |
| GGUF | Q4_K_S | 7.1 | fast, recommended |
| GGUF | Q4_K_M | 7.5 | fast, recommended |
| GGUF | Q5_K_S | 8.4 | |
| GGUF | Q5_K_M | 8.6 | |
| GGUF | Q6_K | 9.9 | very good quality |
| GGUF | Q8_0 | 12.8 | fast, best quality |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
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.