Quick start
ollama run nomic-embed-text:137m-v1.5-fp16Runnable variants
Memory is a rough file-size estimate; context length, runtime and GPU offload change it.
3 of 3 matching variants shown.3 of 3 variants shown.
| Tag | Type | Inputs | Digest | Download | Parameters | Quantization | Context | Est. memory | Run |
|---|---|---|---|---|---|---|---|---|---|
| 137m-v1.5-fp16 | Typelocal | Inputstext | Digest0a109f422b47 | Download274 MB | Parameters137m | QuantizationFP16 | Context2K | Est. memory≈ 1.5 GB | ollama run nomic-embed-text:137m-v1.5-fp16 |
| latest | Typelocal | Inputstext | Digest0a109f422b47 | Download274 MB | ParametersUnknown | QuantizationUnknown | Context2K | Est. memory≈ 1.5 GB | ollama run nomic-embed-text:latest |
| v1.5 | Typelocal | Inputstext | Digest0a109f422b47 | Download274 MB | ParametersUnknown | QuantizationUnknown | Context2K | Est. memory≈ 1.5 GB | ollama run nomic-embed-text:v1.5 |
Related models
embeddinggemma-2local
EmbeddingGemma 2 is a multimodal embedding model from Google built on the Gemma 4 architecture.
embeddinggemmalocal
EmbeddingGemma is a 300M parameter embedding model from Google.
paraphrase-multilinguallocal
Sentence-transformers model that can be used for tasks like clustering or semantic search.
qwen3-embeddinglocal
Building upon the foundational models of the Qwen3 series, Qwen3 Embedding provides a comprehensive range of text embeddings models in various sizes