Can Qwen 3 30B A3B run on MacBook Pro M2 Pro 32GB?
YES — With Offload
Qwen 3 30B A3B needs ~24.4 GB VRAM. MacBook Pro M2 Pro 32GB has 23.0 GB. With Q4_K_M quantization, expect ~19 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
1.4 GB over capacity — needs offload or smaller quantization
Fit status
Runs with offload (needs ~1.1 GB host RAM)
Decode
19.0 tok/s
TTFT
10169 ms
Safe context
4K
Memory
24.4 GB / 23.0 GB
Offload
10%
Memory breakdown
See how fast it feels
What limits this setup
It fits through host-memory offload, and offload is the main reason performance drops.
CPU or host-memory offload is active
About 10% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
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
Remove offload with more accelerator memory
Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Increase host RAM if you keep offloading
This setup may need roughly 1.1 GB of extra host RAM just for the offloaded portion, before OS and other tools.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs with offload (needs ~0.5 GB host RAM) | 20.0 tok/s | 5287 ms | 4K |
| Coding | A | Runs with offload (needs ~1.1 GB host RAM) | 19.0 tok/s | 10169 ms | 4K |
| Agentic Coding | A | Very compromised (needs ~2 GB host RAM) | 17.5 tok/s | 16049 ms | 4K |
| Reasoning | A | Runs with offload (needs ~1.1 GB host RAM) | 19.0 tok/s | 12018 ms | 4K |
| RAG | A | Very compromised (needs ~2 GB host RAM) | 17.5 tok/s | 20062 ms | 4K |
Quantization options
How Qwen 3 30B A3B (30.5B params) fits at each quantization level on MacBook Pro M2 Pro 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 11.9 GB | Low | S91 |
Q3_K_S | 3 | 14.9 GB | Low | S90 |
NVFP4Best for your GPU | 4 | 17.1 GB | Medium | S90 |
Q4_K_M | 4 | 18.6 GB | Medium | F0 |
Q5_K_M | 5 | 22.0 GB | High | F0 |
Q6_K | 6 | 25.0 GB | High | F0 |
Q8_0 | 8 | 32.6 GB | Very High | F0 |
F16 | 16 | 62.5 GB | Maximum | F0 |
Get started
Copy-paste commands to run Qwen 3 30B A3B on your machine.
Run
ollama run qwen3:30b-a3bYour hardware
More models your MacBook Pro M2 Pro 32GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 👁 Alibaba Qwen 3.5 35B A3B | 35B | A | 16.6 tok/s |
