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Models / bge-small-en
2 models (~33M to ~33M) · ↓ 58.9M downloads a month · from $0.08/h on GTX 1660 SUPER right now. Each model's versions do the same job; quantized ones (AWQ, FP8, 4-bit) need less GPU memory and run on cheaper machines.
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| OriginalBAAI/bge-small-en-v1.5 | Text Embeddings Inference | 70 MB | 1.6 GB | $0.08/h GTX 1660 SUPER |
| Main (Xenova)Xenova/bge-small-en-v1.5 | ONNX Runtime | 30 MB | 1.1 GB | $0.08/h GTX 1660 SUPER |
| ONNX (onnx-community)onnx-community/bge-small-en-v1.5-ONNX | ONNX Runtime | 30 MB | 1.1 GB | $0.08/h GTX 1660 SUPER |
| ecommerce product search embeddings (albertobarnabo)albertobarnabo/ecommerce-product-search-embeddings | Text Embeddings Inference | 70 MB | 1.6 GB | $0.08/h GTX 1660 SUPER |
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| OriginalBAAI/bge-small-en | Text Embeddings Inference | 70 MB | 1.6 GB | $0.08/h GTX 1660 SUPER |
Model details come from Hugging Face and are refreshed daily; prices follow the live offers. GPU memory is GridPup's estimate: the weights, room for an 8,192-token conversation (chat models) and the runtime's own memory. Large models are split across the GPUs of one machine ("4x RTX 4090").