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Models / FastContext-1.0
GPU memory needed (smallest version of each): FastContext-1.0 4B about 12.1 GB. The cheapest runs on Nvidia V100 from $0.12/h right now.
2 models (4B to 4B) · ↓ 0 downloads a month · from $0.12/h on Nvidia V100 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 |
|---|---|---|---|---|
| Main (Prince-1)Prince-1/FastContext-1.0-4B-RL | ONNX Runtime GenAI | 8.1 GB | 12.1 GB | $0.12/h Nvidia V100 |
| Main (onnx-community)onnx-community/FastContext-1.0-4B-RL | ONNX Runtime GenAI | 8.1 GB | 12.1 GB | $0.12/h Nvidia V100 |
| Version | Runtime | Weights | GPU memory | Cheapest machine now |
|---|---|---|---|---|
| Main (Prince-1)Prince-1/FastContext-1.0-4B-SFT | ONNX Runtime GenAI | 8.1 GB | 12.1 GB | $0.12/h Nvidia V100 |
| Main (onnx-community)onnx-community/FastContext-1.0-4B-SFT | ONNX Runtime GenAI | 8.1 GB | 12.1 GB | $0.12/h Nvidia V100 |
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").