Can it run?
Runs well
Using Q4_K_M in Ollama
Fit status
Runs well
Decode
81.6 tok/s
TTFT
2373 ms
Safe context
25K
Memory
83.1 GB / 128.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | B | Runs well | 88.4 tok/s | 3186 ms | 48K |
| Chat | B | Runs well | 88.4 tok/s | 1195 ms | 13K |
| Coding | B | Runs well | 81.6 tok/s | 2373 ms | 25K |
| RAG | B | Runs well | 88.4 tok/s | 3983 ms | 48K |
| Reasoning | B | Runs well | 88.4 tok/s | 2589 ms | 25K |
How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on AMD Instinct MI250X 128GB (128.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 42.5 GB | Low | D36 |
Q3_K_S | 3 | 53.4 GB | Low | D38 |
NVFP4 | 4 |
ollama run llama-4-scout-17b-16ehuggingface-cli download llama-4-scout-17b-16e61.0 GB |
| Medium |
| D40 |
Q4_K_M | 4 | 66.5 GB | Medium | C40 |
Q5_K_M | 5 | 78.5 GB | High | C42 |
Q6_KBest for your GPU | 6 | 89.4 GB | High | C44 |
Q8_0 | 8 | 116.6 GB | Very High | C44 |
F16 | 16 | 223.5 GB | Maximum | F0 |