AMD Instinct MI250X 128GBBudget pick
C58.5 tok/s decode
~$15,000 MSRP
Can it run?
Runs well
Using Q4_K_M in Ollama
Fit status
Runs well
Decode
10.9 tok/s
TTFT
17816 ms
Safe context
21K
Memory
68.7 GB / 92.2 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Tight fit | 10.9 tok/s | 25914 ms | 37K |
| Chat | C | Runs well | 10.9 tok/s | 9718 ms | 12K |
| Coding | C | Runs well | 10.9 tok/s | 17816 ms | 21K |
| RAG | C | Tight fit | 10.9 tok/s | 32393 ms | 37K |
| Reasoning | C | Runs well | 10.9 tok/s | 21056 ms | 21K |
How Llama 3.3 70B (70B params) fits at each quantization level on Mac Studio M2 Ultra 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 27.3 GB | Low | D36 |
Q3_K_S | 3 | 34.3 GB | Low | D37 |
NVFP4 | 4 | 39.2 GB | Medium | D39 |
Q4_K_M | 4 | 42.7 GB | Medium | D39 |
Q5_K_M | 5 | 50.4 GB | High | C41 |
Q6_K | 6 | 57.4 GB | High | C43 |
Q8_0Best for your GPU | 8 | 74.9 GB | Very High | C44 |
F16 | 16 | 143.5 GB | Maximum | F0 |
ollama run llama-3.3-70bhuggingface-cli download llama-3.3-70bUpgrade options
~$15,000 MSRP
~$15,000 MSRP
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