mradermacher/EXAONE-4.5-33B-i1-GGUF overview
About < quantize version: 2 < output tensor quantised: 1 < convert type: hf < vocab type: < tags: nicoboss < quants: Q2 K IQ3 M Q4 K S IQ3 XXS Q3 K M small IQ4…
Runs locally from ~14.3 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| EXAONE-4.5-33B.i1-IQ3_M.gguf | GGUF | IQ3_M | 13.92 GB | Download |
| EXAONE-4.5-33B.i1-IQ3_S.gguf | GGUF | IQ3_S | 13.57 GB | Download |
| EXAONE-4.5-33B.i1-IQ4_XS.gguf | GGUF | IQ4_XS | 16.63 GB | Download |
| EXAONE-4.5-33B.i1-Q2_K.gguf | GGUF | Q2_K | 11.57 GB | Download |
| EXAONE-4.5-33B.i1-Q3_K_L.gguf | GGUF | Q3_K_L | 16.21 GB | Download |
| EXAONE-4.5-33B.i1-Q3_K_M.gguf | GGUF | Q3_K_M | 14.97 GB | Download |
| EXAONE-4.5-33B.i1-Q3_K_S.gguf | GGUF | Q3_K_S | 13.53 GB | Download |
| EXAONE-4.5-33B.i1-Q4_0.gguf | GGUF | Q4_0 | 17.58 GB | Download |
| EXAONE-4.5-33B.i1-Q4_1.gguf | GGUF | Q4_1 | 19.40 GB | Download |
| EXAONE-4.5-33B.i1-Q4_K_M.gguf | GGUF | Q4_K_M | 18.67 GB | Download |
| EXAONE-4.5-33B.i1-Q4_K_S.gguf | GGUF | Q4_K_S | 17.65 GB | Download |
| EXAONE-4.5-33B.i1-Q5_K_M.gguf | GGUF | Q5_K_M | 21.87 GB | Download |
| EXAONE-4.5-33B.i1-Q5_K_S.gguf | GGUF | Q5_K_S | 21.28 GB | Download |
| EXAONE-4.5-33B.i1-Q6_K.gguf | GGUF | Q6_K | 25.27 GB | Download |
| EXAONE-4.5-33B.imatrix.gguf | GGUF | GGUF | 14.3 MB | Download |
Model Details
| Model ID | mradermacher/EXAONE-4.5-33B-i1-GGUF |
|---|---|
| Author | mradermacher |
| Pipeline | — |
| License | other |
| Base model | LGAI-EXAONE/EXAONE-4.5-33B |
| Last modified | 2026-07-08T00:23:41.000Z |
Model README
---
base_model: LGAI-EXAONE/EXAONE-4.5-33B
language:
- en
- ko
- es
- de
- ja
- vi
library_name: transformers
license: other
license_link: LICENSE
license_name: exaone
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- lg-ai
- exaone
---
About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
<!-- ### quants: Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->
<!-- ### quants_skip: -->
<!-- ### skip_mmproj: -->
weighted/imatrix quants of https://huggingface.co/LGAI-EXAONE/EXAONE-4.5-33B
<!-- provided-files -->
For a convenient overview and download list, visit our model page for this model.
static quants are available at https://huggingface.co/mradermacher/EXAONE-4.5-33B-GGUF
This is a vision model - mmproj files (if any) will be in the static repository.
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 | imatrix | 0.1 | imatrix file (for creating your own quants) |
| GGUF | i1-Q2_K | 12.5 | IQ3_XXS probably better |
| GGUF | i1-Q3_K_S | 14.6 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 14.7 | beats Q3_K* |
| GGUF | i1-IQ3_M | 15.0 | |
| GGUF | i1-Q3_K_M | 16.2 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 17.5 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 18.0 | |
| GGUF | i1-Q4_0 | 19.0 | fast, low quality |
| GGUF | i1-Q4_K_S | 19.1 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 20.1 | fast, recommended |
| GGUF | i1-Q4_1 | 20.9 | |
| GGUF | i1-Q5_K_S | 22.9 | |
| GGUF | i1-Q5_K_M | 23.6 | |
| GGUF | i1-Q6_K | 27.2 | practically like static Q6_K |
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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
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