MacBook Pro M4 32GBBudget pick
C90.7 tok/s decode
~$799 MSRP
Can it run?
Runs well
Using Q6_K in Ollama
Fit status
Runs well
Decode
435.5 tok/s
TTFT
445 ms
Safe context
64K
Memory
4.0 GB / 16.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Runs well | 356.8 tok/s | 789 ms | 128K |
| Chat | C | Runs well | 356.8 tok/s | 350 ms | 32K |
| Coding | C | Runs well | 435.5 tok/s | 445 ms | 64K |
| RAG | C | Runs well | 356.8 tok/s | 986 ms | 128K |
| Reasoning | C | Runs well | 356.8 tok/s | 641 ms | 64K |
How SmolVLM 500M Instruct (0.5B params) fits at each quantization level on Radeon RX 7900M 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.2 GB | Low | D30 |
Q3_K_S | 3 | 0.2 GB | Low | D30 |
NVFP4 | 4 |
huggingface-cli download hf-ggml-org--smolvlm-500m-instruct-ggufUpgrade options
~$799 MSRP
~$1,099 MSRP
0.3 GB |
| Medium |
| D30 |
Q4_K_M | 4 | 0.3 GB | Medium | D30 |
Q5_K_M | 5 | 0.4 GB | High | D30 |
Q6_K | 6 | 0.4 GB | High | D30 |
Q8_0 | 8 | 0.5 GB | Very High | D30 |
F16Best for your GPU | 16 | 1.0 GB | Maximum | D31 |
~$1,999 MSRP