mradermacher/Trinity-Mini-GGUF overview
About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: < quants: x f16 Q4 K S Q2 K Q8 0 Q6 K Q3 K M Q3 K S Q3 K L Q4…
Runs locally from ~9.01 GB disk (12 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Trinity-Mini.IQ4_XS.gguf | GGUF | GGUF | 13.16 GB | Download |
| Trinity-Mini.Q2_K.gguf | GGUF | GGUF | 9.01 GB | Download |
| Trinity-Mini.Q3_K_L.gguf | GGUF | GGUF | 12.66 GB | Download |
| Trinity-Mini.Q3_K_M.gguf | GGUF | GGUF | 11.68 GB | Download |
| Trinity-Mini.Q3_K_S.gguf | GGUF | GGUF | 10.64 GB | Download |
| Trinity-Mini.Q4_K_M.gguf | GGUF | GGUF | 14.74 GB | Download |
| Trinity-Mini.Q4_K_S.gguf | GGUF | GGUF | 13.88 GB | Download |
| Trinity-Mini.Q5_K_M.gguf | GGUF | GGUF | 17.28 GB | Download |
| Trinity-Mini.Q5_K_S.gguf | GGUF | GGUF | 16.81 GB | Download |
| Trinity-Mini.Q6_K.gguf | GGUF | GGUF | 19.99 GB | Download |
| Trinity-Mini.Q8_0.gguf | GGUF | GGUF | 25.88 GB | Download |
Model Details
| Model ID | mradermacher/Trinity-Mini-GGUF |
|---|---|
| Author | mradermacher |
| Pipeline | — |
| License | other |
| Base model | arcee-ai/Trinity-Mini |
| Last modified | 2026-06-23T16:34:19.000Z |
Model README
---
base_model: arcee-ai/Trinity-Mini
language:
- en
- es
- fr
- de
- it
- pt
- ru
- ar
- hi
- ko
- zh
library_name: transformers
license: other
license_link: LICENSE
license_name: openmdw-1.1
mradermacher:
readme_rev: 1
quantized_by: mradermacher
---
About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
<!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
static quants of https://huggingface.co/arcee-ai/Trinity-Mini
<!-- provided-files -->
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Trinity-Mini-i1-GGUF
Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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 | 9.8 | |
| GGUF | Q3_K_S | 11.5 | |
| GGUF | Q3_K_M | 12.6 | lower quality |
| GGUF | Q3_K_L | 13.7 | |
| GGUF | IQ4_XS | 14.2 | |
| GGUF | Q4_K_S | 15.0 | fast, recommended |
| GGUF | Q4_K_M | 15.9 | fast, recommended |
| GGUF | Q5_K_S | 18.1 | |
| GGUF | Q5_K_M | 18.7 | |
| GGUF | Q6_K | 21.6 | very good quality |
| GGUF | Q8_0 | 27.9 | 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.
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