devquasar/nvidia.llama-3.3-nemotron-70b-reward-principle-gguf - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.
Model Intelligence Sheet
devquasar/nvidia.llama-3.3-nemotron-70b-reward-principle-gguf overview
'Make knowledge free for everyone' Quantized version of: nvidia/Llama-3.3-Nemotron-70B-Reward-Principle
Downloads
103
Likes
0
Pipeline
text-generation
Library
—
Visibility
Public
Access
Open
Repository Files & Downloads
24 files detected
Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Llama-3.3-Nemotron-70B-Reward-Principle_imatrix.gguf | GGUF | — | 23.83 MB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.IQ1_M.gguf | GGUF | IQ1_M | 15.60 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.IQ2_XS.gguf | GGUF | IQ2_XS | 19.69 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q2_K.gguf | GGUF | Q2_K | 24.56 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q3_K_M.gguf | GGUF | Q3_K_M | 31.91 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q4_K_M-00001-of-00004.gguf | GGUF | Q4_K_M | 13.03 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q4_K_M-00002-of-00004.gguf | GGUF | Q4_K_M | 12.95 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q4_K_M-00003-of-00004.gguf | GGUF | Q4_K_M | 12.99 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q4_K_M-00004-of-00004.gguf | GGUF | Q4_K_M | 644.88 MB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q5_K_M-00001-of-00004.gguf | GGUF | Q5_K_M | 12.93 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q5_K_M-00002-of-00004.gguf | GGUF | Q5_K_M | 12.99 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q5_K_M-00003-of-00004.gguf | GGUF | Q5_K_M | 12.99 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q5_K_M-00004-of-00004.gguf | GGUF | Q5_K_M | 7.60 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q6_K-00001-of-00005.gguf | GGUF | Q6_K | 13.02 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q6_K-00002-of-00005.gguf | GGUF | Q6_K | 12.90 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q6_K-00003-of-00005.gguf | GGUF | Q6_K | 13.02 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q6_K-00004-of-00005.gguf | GGUF | Q6_K | 13.02 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q6_K-00005-of-00005.gguf | GGUF | Q6_K | 1.95 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q8_0-00001-of-00006.gguf | GGUF | — | 12.86 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q8_0-00002-of-00006.gguf | GGUF | — | 13.01 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q8_0-00003-of-00006.gguf | GGUF | — | 13.01 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q8_0-00004-of-00006.gguf | GGUF | — | 12.93 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q8_0-00005-of-00006.gguf | GGUF | — | 13.01 GB | Download |
| nvidia.Llama-3.3-Nemotron-70B-Reward-Principle.Q8_0-00006-of-00006.gguf | GGUF | — | 5.01 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
{
"metadata": {},
"card_data": {
"base_model": [
"nvidia/Llama-3.3-Nemotron-70B-Reward-Principle"
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"pipeline_tag": "text-generation",
"frontmatter": {
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"nvidia/Llama-3.3-Nemotron-70B-Reward-Principle"
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"pipeline_tag": "text-generation"
},
"hero_image_url": "https://raw.githubusercontent.com/csabakecskemeti/devquasar/main/dq_logo_black-transparent.png",
"summary": "'Make knowledge free for everyone' Quantized version of: nvidia/Llama-3.3-Nemotron-70B-Reward-Principle",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nbase_model:\n- nvidia/Llama-3.3-Nemotron-70B-Reward-Principle\npipeline_tag: text-generation\n---\n\n[<img src=\"https://raw.githubusercontent.com/csabakecskemeti/devquasar/main/dq_logo_black-transparent.png\" width=\"200\"/>](https://devquasar.com)\n\n'Make knowledge free for everyone'\n\nQuantized version of: [nvidia/Llama-3.3-Nemotron-70B-Reward-Principle](https://huggingface.co/nvidia/Llama-3.3-Nemotron-70B-Reward-Principle)\n<a href='https://ko-fi.com/L4L416YX7C' target='_blank'><img height='36' style='border:0px;height:36px;' src='https://storage.ko-fi.com/cdn/kofi6.png?v=6' border='0' alt='Buy Me a Coffee at ko-fi.com' /></a>\n",
"related_quantizations": []
},
"tags": [
"gguf",
"text-generation",
"base_model:nvidia/Llama-3.3-Nemotron-70B-Reward-Principle",
"base_model:quantized:nvidia/Llama-3.3-Nemotron-70B-Reward-Principle",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 0,
"downloads": 103,
"gated": false,
"private": false,
"last_modified": "2025-11-03T04:09:11.000Z",
"created_at": "2025-11-02T19:47:19.000Z",
"pipeline_tag": "text-generation",
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}
Source payload excerpt (from Hugging Face API)
{
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"id": "DevQuasar/nvidia.Llama-3.3-Nemotron-70B-Reward-Principle-GGUF",
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"sha": "faff134d7ed5da4589a5fb36d3a15256be3be0d0",
"createdAt": "2025-11-02T19:47:19.000Z",
"lastModified": "2025-11-03T04:09:11.000Z",
"author": "DevQuasar",
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"siblings_count": 26
}