MacBook Pro M3 Max 128GBBudget pick
C252 tok/s decode
~$2,499 MSRP
Can it run?
Runs well
Using Q6_K in Ollama
Fit status
Runs well
Decode
1764.0 tok/s
TTFT
350 ms
Safe context
123K
Memory
10.4 GB / 80.0 GB
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Agentic Coding | C | Runs well | 1764.0 tok/s | 350 ms | 246K |
| Chat | C | Runs well | 1764.0 tok/s | 350 ms | 61K |
| Coding | C | Runs well | 1764.0 tok/s | 350 ms | 123K |
| RAG | C | Runs well | 1764.0 tok/s | 350 ms | 246K |
| Reasoning | C | Runs well | 1764.0 tok/s | 350 ms | 123K |
How SmolVLM 500M Instruct (0.5B params) fits at each quantization level on NVIDIA H100 PCIe 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.2 GB | Low | D29 |
Q3_K_S | 3 | 0.2 GB | Low | D29 |
NVFP4 | 4 | 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 | D30 |
huggingface-cli download hf-ggml-org--smolvlm-500m-instruct-ggufUpgrade options
~$2,499 MSRP
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~$3,999 MSRP