Can Qwen3-VL 30B A3B Instruct run on Mac mini M4 64GB?
YES — Runs Great
Qwen3-VL 30B A3B Instruct needs ~28.5 GB VRAM. Mac mini M4 64GB has 46.1 GB. With Q4_K_M quantization, expect ~14 tok/s.
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
13.5 tok/s
TTFT
14328 ms
Safe context
208K
Memory
28.5 GB / 46.1 GB
Memory breakdown
See how fast it feels
What limits this setup
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 13.5 tok/s | 7815 ms | 208K |
| Coding | S | Runs well | 13.5 tok/s | 14328 ms | 208K |
| Agentic Coding | S | Runs well | 13.5 tok/s | 20841 ms | 208K |
| Reasoning | S | Runs well | 13.5 tok/s | 16934 ms | 208K |
| RAG | S | Runs well | 13.5 tok/s | 26052 ms | 208K |
Quantization options
How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on Mac mini M4 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.7 GB | Low | S86 |
Q3_K_S | 3 | 14.7 GB | Low | S87 |
NVFP4 | 4 | 16.8 GB | Medium | S88 |
Q4_K_M | 4 | 18.3 GB | Medium | S88 |
Q5_K_M | 5 | 21.6 GB | High | S89 |
Q6_K | 6 | 24.6 GB | High | S91 |
Q8_0Best for your GPU | 8 | 32.1 GB | Very High | S90 |
F16 | 16 | 61.5 GB | Maximum | F0 |
Get started
Copy-paste commands to run Qwen3-VL 30B A3B Instruct on your machine.
Run
lms load Qwen3-VL-30B-A3B-Instruct && lms server startYour hardware
