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Models / MNLP_M2_document_encoder
GPU memory needed (smallest version of each): MNLP_M2_document_encoder ~335M about 2.4 GB. The cheapest runs on GTX 1660 SUPER from $0.07/h right now.
1 model (~335M) · ↓ 144 downloads a month · from $0.07/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 |
|---|---|---|---|---|
| Originalimaneb942/MNLP_M2_document_encoder | Text Embeddings Inference | 670 MB | 2.4 GB | $0.07/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").