Publish Nemotron-3-Embed-1B Q4_K_M GGUF

Independent llama.cpp b10015 conversion of nvidia/Nemotron-3-Embed-1B-BF16 at revision 0677b2025cbc37daf92d7b9c7a225de8cfbc5b0b. Includes OpenMDW-1.1 license, NVIDIA notices, exact checksum, conversion provenance, LM Studio instructions, limitations, and validation results.

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+nemotron-3-embed-1b-q4_k_m.gguf filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,55 @@
+All binary model files and source code files are licensed under the OpenMDW-1.1 License.
+
+------------
+Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+
+
+OpenMDW License Agreement, version 1.1 (OpenMDW-1.1)
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NOTICE

@@ -0,0 +1,5 @@
+mistralai/Ministral-3-3B-Instruct-2512 is licensed under the Apache-2.0 License.
+
+- You must cause any modified files to carry prominent notices stating that You changed the files.
+- You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works.
+- If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License.

QUANTIZATION.md

@@ -0,0 +1,72 @@
+# Quantization and reproducibility record
+
+## Source
+
+- Model: `nvidia/Nemotron-3-Embed-1B-BF16`
+- Revision: `0677b2025cbc37daf92d7b9c7a225de8cfbc5b0b`
+- Source format: BF16 Safetensors
+- Upstream license: OpenMDW License Agreement 1.1
+
+## Toolchain
+
+- Project: `ggml-org/llama.cpp`
+- Tag/build: `b10015`
+- Commit: `12127defda4f41b7679cb2477a4b0d65ee6a0c8f`
+- Converter: `convert_hf_to_gguf.py`
+- Quantizer: `llama-quantize`
+- Importance matrix: none
+
+Equivalent command outline (local paths omitted):
+
+```bash
+python convert_hf_to_gguf.py \
+  nvidia--Nemotron-3-Embed-1B-BF16-snapshot \
+  --outfile nemotron-3-embed-1b-f16.gguf \
+  --outtype f16
+
+llama-quantize \
+  nemotron-3-embed-1b-f16.gguf \
+  nemotron-3-embed-1b-q4_k_m.gguf \
+  Q4_K_M
+```
+
+## Output identity
+
+- File: `nemotron-3-embed-1b-q4_k_m.gguf`
+- Size: `749352096` bytes
+- SHA-256: `9a74166f51dbc280073748fa199bea49283bd21f7f9280f2dec2b4d975ddfd1d`
+- GGUF version: 3
+- Quantization version: 2
+- GGUF file type: 15 (`Q4_K_M`)
+- Tensor count: 146
+- Metadata/data boundary: byte `7869600`
+
+Selected embedded architecture metadata:
+
+| Key | Value |
+|---|---:|
+| `general.architecture` | `mistral3` |
+| `general.name` | `nvidia/Nemotron-3-Embed-1B-BF16` |
+| `general.finetune` | `0677b2025cbc37daf92d7b9c7a225de8cfbc5b0b` |
+| `mistral3.block_count` | 16 |
+| `mistral3.context_length` | 262144 |
+| `mistral3.embedding_length` | 2048 |
+| `mistral3.feed_forward_length` | 6144 |
+| `mistral3.attention.head_count` | 24 |
+| `mistral3.attention.head_count_kv` | 8 |
+| `mistral3.attention.causal` | false |
+| `mistral3.pooling_type` | 1 (mean) |
+| `mistral3.vocab_size` | 131072 |
+
+## Integrity check
+
+```bash
+shasum -a 256 nemotron-3-embed-1b-q4_k_m.gguf
+```
+
+Expected output:
+
+```text
+9a74166f51dbc280073748fa199bea49283bd21f7f9280f2dec2b4d975ddfd1d  nemotron-3-embed-1b-q4_k_m.gguf
+```
+

README.md

@@ -1,3 +1,165 @@
 ---
 license: openmdw-1.1
+base_model: nvidia/Nemotron-3-Embed-1B-BF16
+base_model_relation: quantized
+library_name: gguf
+pipeline_tag: sentence-similarity
+language:
+  - multilingual
+  - en
+  - ar
+  - as
+  - bn
+  - bg
+  - zh
+  - da
+  - nl
+  - fi
+  - fr
+  - de
+  - hi
+  - id
+  - it
+  - ja
+  - ko
+  - ms
+  - mr
+  - ne
+  - "no"
+  - fa
+  - pt
+  - ro
+  - ru
+  - es
+  - sw
+  - sv
+  - ta
+  - te
+  - th
+  - uk
+  - ur
+  - vi
+tags:
+  - gguf
+  - Q4_K_M
+  - text-embeddings
+  - feature-extraction
+  - retrieval
+  - semantic-search
+  - rag
+  - lm-studio
+  - llama-cpp
+  - arxiv:2407.14679
+  - arxiv:2502.13595
 ---
+
+# Nemotron-3-Embed-1B Q4_K_M GGUF
+
+An independently converted and quantized GGUF of NVIDIA's
+[`nvidia/Nemotron-3-Embed-1B-BF16`](https://huggingface.co/nvidia/Nemotron-3-Embed-1B-BF16),
+prepared for local embedding inference in LM Studio and llama.cpp-compatible runtimes.
+
+This repository is not an official NVIDIA release and is not affiliated with or endorsed by NVIDIA.
+
+## File
+
+| File | Quantization | Size | SHA-256 |
+|---|---:|---:|---|
+| `nemotron-3-embed-1b-q4_k_m.gguf` | Q4_K_M | 749,352,096 bytes (714.6 MiB) | `9a74166f51dbc280073748fa199bea49283bd21f7f9280f2dec2b4d975ddfd1d` |
+
+The model produces 2,048-dimensional, L2-normalized embeddings. Its GGUF metadata declares a
+262,144-token maximum context. The release was functionally tested at a 4,096-token context; very
+large contexts were not validated and require substantially more memory.
+
+## Use with LM Studio
+
+Download the GGUF from **Files and versions**, then drag it into LM Studio or place it in LM Studio's
+models directory. LM Studio should classify it as an embedding model.
+
+Load it with a 4,096-token context and full GPU offload, start the local server, and call the
+OpenAI-compatible embeddings endpoint:
+
+```bash
+curl http://127.0.0.1:1234/v1/embeddings \
+  -H 'Content-Type: application/json' \
+  -d '{
+    "model": "nemotron-3-embed-1b-q4",
+    "input": [
+      "query: What is retrieval-augmented generation?",
+      "passage: Retrieval-augmented generation adds retrieved documents to a model prompt."
+    ]
+  }'
+```
+
+The exact model identifier can differ if LM Studio assigns another load name; check
+`http://127.0.0.1:1234/v1/models` when needed.
+
+## Retrieval format
+
+Use the prefixes specified by NVIDIA:
+
+- Queries: `query: <text>`
+- Documents: `passage: <text>`
+
+Embeddings are normalized, so cosine similarity and dot product give equivalent rankings (within
+normal floating-point tolerance).
+
+## Conversion provenance
+
+- Upstream repository: [`nvidia/Nemotron-3-Embed-1B-BF16`](https://huggingface.co/nvidia/Nemotron-3-Embed-1B-BF16)
+- Exact upstream revision: [`0677b2025cbc37daf92d7b9c7a225de8cfbc5b0b`](https://huggingface.co/nvidia/Nemotron-3-Embed-1B-BF16/commit/0677b2025cbc37daf92d7b9c7a225de8cfbc5b0b)
+- Conversion and quantization: [`llama.cpp`](https://github.com/ggml-org/llama.cpp) build `b10015`, commit [`12127defda4f41b7679cb2477a4b0d65ee6a0c8f`](https://github.com/ggml-org/llama.cpp/commit/12127defda4f41b7679cb2477a4b0d65ee6a0c8f)
+- Conversion path: upstream BF16 Safetensors → F16 GGUF → Q4_K_M GGUF
+- Importance matrix: none
+- Output GGUF version: 3
+- Quantization version: 2
+
+The conversion was mechanical. The model was not fine-tuned or otherwise trained. See
+[`QUANTIZATION.md`](QUANTIZATION.md) for the reproducibility record and embedded metadata summary.
+
+## Validation
+
+Validated on an Apple M3 Max with LM Studio 0.4.19 Build 2 and its llama.cpp runtime 2.25.2, using
+full GPU offload and a 4,096-token context.
+
+| Check | Result |
+|---|---:|
+| Output dimensions | 2,048 |
+| L2 norm (three test vectors) | 1.00000002 / 1.00000001 / 0.99999997 |
+| Relevant query/passage cosine | 0.654999 |
+| Unrelated query/passage cosine | 0.044103 |
+| Median latency, one input | 30.46 ms |
+| Median batch time, 32 inputs | 974.98 ms |
+| Median batch throughput | 32.82 texts/s |
+
+Latency includes local HTTP and JSON serialization. These numbers are a runtime smoke test, not a
+retrieval-quality evaluation. Hardware, text length, context settings, and runtime versions affect
+performance.
+
+## Limitations
+
+- Q4_K_M is lossy and can change retrieval scores or rankings relative to the upstream BF16 model.
+- No MTEB/MMTEB accuracy evaluation was run on this quantization; consult NVIDIA's upstream model
+  card for BF16 benchmark results.
+- This model is intended for embeddings, retrieval, semantic search, and reranking pipelines. It is
+  not a chat or text-generation model.
+- Users remain responsible for evaluating model behavior, data handling, and suitability for their
+  application.
+
+## License and attribution
+
+The model materials are distributed under the
+[OpenMDW License Agreement 1.1](https://openmdw.ai/license/1-1/). The upstream model incorporates
+Ministral-3-3B-Instruct-2512 materials released under Apache 2.0.
+
+This repository retains NVIDIA's [`LICENSE`](LICENSE), [`NOTICE`](NOTICE), and
+[`THIRD_PARTY_NOTICES.md`](THIRD_PARTY_NOTICES.md). By using or distributing the model, you agree to
+the applicable license terms. NVIDIA retains ownership of its names and trademarks; their use here
+is solely to identify the upstream model.
+
+## Upstream resources
+
+- [NVIDIA upstream model card](https://huggingface.co/nvidia/Nemotron-3-Embed-1B-BF16)
+- [NVIDIA Nemotron-3-Embed blog post](https://huggingface.co/blog/nvidia/nemotron-3-embed-wins-rteb)
+- [Compact Language Models via Pruning and Knowledge Distillation](https://arxiv.org/abs/2407.14679)
+- [MMTEB: Massive Multilingual Text Embedding Benchmark](https://arxiv.org/abs/2502.13595)

SHA256SUMS

@@ -0,0 +1 @@
+9a74166f51dbc280073748fa199bea49283bd21f7f9280f2dec2b4d975ddfd1d  nemotron-3-embed-1b-q4_k_m.gguf

THIRD_PARTY_NOTICES.md

@@ -0,0 +1,471 @@
+Copyright "Hugging Face, Inc." - Apache License 2.0
+
+License Text([https://github.com/huggingface/sentence-transformers/blob/main/LICENSE](https://github.com/huggingface/sentence-transformers/blob/main/LICENSE))
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+Ubiquitous Knowledge Processing (UKP) Lab
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