usermma/Atomight-V2.2-0.5B-UltraThink-GGUF-mradermacher 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 ~322.6 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Atomight-V2.2-0.5B-UltraThink.IQ4_XS.gguf | GGUF | GGUF | 335.2 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q2_K.gguf | GGUF | GGUF | 322.9 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q3_K_L.gguf | GGUF | GGUF | 352.2 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q3_K_M.gguf | GGUF | GGUF | 339.0 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q3_K_S.gguf | GGUF | GGUF | 322.6 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q4_K_M.gguf | GGUF | GGUF | 379.4 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q4_K_S.gguf | GGUF | GGUF | 367.6 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q5_K_M.gguf | GGUF | GGUF | 400.6 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q5_K_S.gguf | GGUF | GGUF | 393.6 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q6_K.gguf | GGUF | GGUF | 482.3 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.Q8_0.gguf | GGUF | GGUF | 506.5 MB | Download |
| Atomight-V2.2-0.5B-UltraThink.f16.gguf | GGUF | GGUF | 948.1 MB | Download |
Model Details
Model README
---
base_model: NovatasticRoScript/Atomight-V2.2-UltraThink-0.5B
datasets:
- bespokelabs/Bespoke-Stratos-17k
- open-thoughts/OpenThoughts-114k
- angrygiraffe/claude-opus-4.6-4.7-reasoning-8.7k
- allenai/ai2_arc
- allenai/hellaswag
- Rowan/hellaswag
- TIGER-Lab/MMLU-Pro
- CohereLabs/Global-MMLU
language:
- en
library_name: transformers
license: mit
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
---
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/NovatasticRoScript/Atomight-V2.2-UltraThink-0.5B
<!-- provided-files -->
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
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 | Q3_K_S | 0.4 | |
| GGUF | Q2_K | 0.4 | |
| GGUF | IQ4_XS | 0.5 | |
| GGUF | Q3_K_M | 0.5 | lower quality |
| GGUF | Q3_K_L | 0.5 | |
| GGUF | Q4_K_S | 0.5 | fast, recommended |
| GGUF | Q4_K_M | 0.5 | fast, recommended |
| GGUF | Q5_K_S | 0.5 | |
| GGUF | Q5_K_M | 0.5 | |
| GGUF | Q6_K | 0.6 | very good quality |
| GGUF | Q8_0 | 0.6 | fast, best quality |
| GGUF | f16 | 1.1 | 16 bpw, overkill |
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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