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Models / snowflake-arctic-embed-m
3 models (~109M to ~305M) · ↓ 620.1K 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 |
|---|---|---|---|---|
| OriginalSnowflake/snowflake-arctic-embed-m | Text Embeddings Inference | 220 MB | 1.8 GB | $0.08/h GTX 1660 SUPER |
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| OriginalSnowflake/snowflake-arctic-embed-m-v1.5 | Text Embeddings Inference | 220 MB | 1.8 GB | $0.08/h GTX 1660 SUPER |
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| OriginalSnowflake/snowflake-arctic-embed-m-v2.0 | ONNX Runtime | 310 MB | 1.5 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").