---
base_model: empero-ai/openNemo-9B-Claude-Opus-4.6-distill
datasets:
- nohurry/Opus-4.6-Reasoning-3000x-filtered
- Jackrong/Qwen3.5-reasoning-700x
- TeichAI/claude-4.5-opus-high-reasoning-250x
- Roman1111111/claude-opus-4.6-10000x
- TeichAI/Claude-Opus-4.6-Reasoning-927x
- dalisoft/claude-opus-4.6-high-reasoning-700x
- Hastagaras/Claude-Sonnet-X-Opus-4.6-Reasoning-small-500
- TeichAI/claude-haiku-4.5-high-reasoning-1700x
- Crownelius/Opus-4.6-Reasoning-3300x
- QuietImpostor/Sao10K-Claude-3-Opus-Instruct-15K-ShareGPT
language:
- en
library_name: transformers
license: other
license_link: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
license_name: nvidia-open-model-license
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
- nvidia
- pytorch
- mamba2
- hybrid
- reasoning
- distillation
- claude-opus
- qlora
- sft
- dpo
- think
---
## About

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<!-- ### 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 -->
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static quants of https://huggingface.co/empero-ai/openNemo-9B-Claude-Opus-4.6-distill

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#openNemo-9B-Claude-Opus-4.6-distill-GGUF).***

weighted/imatrix quants are available at https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-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](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q2_K.gguf) | Q2_K | 5.1 |  |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q3_K_S.gguf) | Q3_K_S | 5.2 |  |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.IQ4_XS.gguf) | IQ4_XS | 5.5 |  |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q3_K_M.gguf) | Q3_K_M | 5.5 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q3_K_L.gguf) | Q3_K_L | 5.6 |  |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q4_K_S.gguf) | Q4_K_S | 6.3 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q4_K_M.gguf) | Q4_K_M | 6.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q5_K_S.gguf) | Q5_K_S | 6.9 |  |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q5_K_M.gguf) | Q5_K_M | 7.2 |  |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q6_K.gguf) | Q6_K | 9.2 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.Q8_0.gguf) | Q8_0 | 9.6 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/openNemo-9B-Claude-Opus-4.6-distill-GGUF/resolve/main/openNemo-9B-Claude-Opus-4.6-distill.f16.gguf) | f16 | 17.9 | 16 bpw, overkill |

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

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

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