nomic-ai/nomic-embed-text-v2-moe
sentence-similarity model by nomic-ai
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Model card & documentation
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Blog | Technical Report | AWS SageMaker | Atlas Embedding and Unstructured Data Analytics Platform This model was presented in the paper Training Sparse Mixture Of Experts Text Embedding Models. nomic-embed-text-v2-moe is a SoTA multilingual MoE text embedding model that excels at multilingual retrieval: Transformer-based text embedding models have improved their performance on benchmarks like MIRACL and BEIR by increasing their parameter counts. However, this scaling approach introduces significant deployment challenges, including increased inference latency and memory usage. These challenges are particularly severe in retrieval-augmented generation (RAG) applications, where large models' increased memory requirements constrain dataset ingestion capacity, and their higher latency directly impacts query-time performance. While causal language models have addressed similar efficiency challenges using Mixture of Experts (MoE) architectures, this approach hasn't been successfully adapted to the general text embedding setting. In this paper, we introduce Nomic Embed v2, the first general purpose MoE text embedding model. Our…
Read the full model card ↗ · Preview checked 2026-10-29T13:36:34.202Z
Inside the original model card — Document outline
- nomic-embed-text-v2-moe: Multilingual Mixture of Experts Text Embeddings
- Model Overview
- Model Architecture
- Paper Abstract
- Usage Guide
- Installation
- Transformers
- SentenceTransformers
- Performance
- Best Practices
- Limitations
- Training Details
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
nomic-ai/nomic-embed-text-v2-moe is a sentence-similarity model repository published by nomic-ai on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 860,288
- Cumulative likes
- 513
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 475,292,928
- Architecture
- NomicBertModel
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2025-02-07T22:50:07.000Z
- Last modified
- 2025-04-01T13:38:53.000Z
Compatibility and lineage
Reported languages: en, es, fr, de, it, pt, pl, nl, tr, ja, vi, ru, id, ar, cs, ro, sv, el, uk, zh, hu, da, no, hi, fi, bg, ko, sk, th, he, ca, lt, fa, ms, sl, lv, mr, bn, sq, cy
Reported base models: nomic-ai/nomic-embed-text-v2-moe-unsupervised
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:31.802Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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