llama-nemotron-embed-1b-v2
The Llama Nemotron Embedding 1B model is optimized for multilingual and cross-lingual text question-answering retrieval with support for long documents (up to 8192 tokens) and dynamic embedding size (Matryoshka Embeddings). This model was evaluated on 26 languages: English, Arabic, Bengali, Chinese, Czech, Danish, Dutch, Finnish, French, German, Hebrew, Hindi, Hungarian, Indonesian, Italian, Japanese, Korean, Norwegi...
Params
1.2 B
Context
131,072
Downloads 30d
429 K
Likes
63
Download history
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Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | bf16 | 2.5 GB | 3.4 GB | ✅ Runs comfortably |
| model.safetensors (bf16, full) | bf16 + 128K ctx | 2.5 GB | 6.2 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- LlamaBidirectionalModel
- Parameters
- 1.2 B
- Tensor type
- BF16
- Context length
- 131,072
- Vocabulary
- 128,256
- Layers / heads
- 16 / 32
- Licence
- other
- First seen on the Hub
- 2025-10-16
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Compare with any feature-extraction model