This page answers Fireredteam Firered Image Edit 1 0 q5_k_m quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.
Short answer: Fireredteam Firered Image Edit 1 0 typically needs around 6GB VRAM at Q5_K_M, and 8GB is safer for smoother usage.
Estimated from Q4 and Q8 requirement bounds using midpoint interpolation.
Throughput data below uses available compatibility measurements/estimates and is sorted by tokens per second for this model.
Need general guidance? Review full methodology.
| GPU | VRAM | Quantization | Speed | Compatibility | Buy |
|---|---|---|---|---|---|
| AMD Instinct MI300X | 192GB | Q4 | 763 tok/s | View full compatibility | Buy options |
| NVIDIA H200 SXM 141GB | 141GB | Q4 | 689 tok/s | View full compatibility | Buy options |
| NVIDIA H100 SXM5 80GB | 80GB | Q4 | 495 tok/s | View full compatibility | Buy options |
| AMD Instinct MI250X | 128GB | Q4 | 478 tok/s | View full compatibility | Buy options |
| NVIDIA H100 PCIe 80GB | 80GB | Q4 | 314 tok/s | View full compatibility | Buy options |
| RTX 5090 | 32GB | Q4 | 300 tok/s | View full compatibility | Buy options |
| NVIDIA A100 80GB SXM4 | 80GB | Q4 | 292 tok/s | View full compatibility | Buy options |
| AMD Instinct MI210 | 64GB | Q4 | 238 tok/s | View full compatibility | Buy options |
| NVIDIA A100 40GB PCIe | 40GB | Q4 | 227 tok/s | View full compatibility | Buy options |
| RTX 4090 | 24GB | Q4 | 180 tok/s | View full compatibility | Buy options |
| NVIDIA RTX 6000 Ada | 48GB | Q4 | 178 tok/s | View full compatibility | Buy options |
| NVIDIA L40 | 48GB | Q4 | 166 tok/s | View full compatibility | Buy options |
Fireredteam Firered Image Edit 1 0 at Q5_K_M is estimated to require about 6GB VRAM minimum, with 8GB recommended for smoother operation.
Start with AMD Instinct MI300X, NVIDIA H200 SXM 141GB, NVIDIA H100 SXM5 80GB and review each compatibility page for full speed and fit details.
Q5_K_M is a balance point between memory usage and quality. If your GPU is below 6GB, consider lower-bit quantization; if you have extra VRAM, compare Q8/FP16 options for quality-sensitive workloads.