Qwen3-VL 30B A3B Instruct needs ~28.5 GB VRAM. MacBook Pro M1 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~34 tok/s.
Operating mode
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
34.4 tok/s
TTFT
5627 ms
Safe context
208K
Memory
28.5 GB / 46.1 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 34.4 tok/s | 3069 ms | 208K |
| Coding | S | Runs well | 34.4 tok/s | 5627 ms | 208K |
| Agentic Coding | S | Runs well | 34.4 tok/s | 8185 ms | 208K |
| Reasoning | S | Runs well | 34.4 tok/s | 6650 ms | 208K |
| RAG | S | Runs well | 34.4 tok/s | 10231 ms | 208K |
How Qwen3-VL 30B A3B Instruct (30B params) fits at each quantization level on MacBook Pro M1 Max 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 |
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
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 33.3 tok/s | |
| Qwen 3.6 35B A3B | 35B | S | 28 tok/s |
Yes, MacBook Pro M1 Max 64GB can run Qwen3-VL 30B A3B Instruct with a S grade (Runs well). Expected decode speed: 34.4 tok/s.
Qwen3-VL 30B A3B Instruct (30B parameters) requires approximately 28.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3-VL 30B A3B Instruct is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M1 Max 64GB, Qwen3-VL 30B A3B Instruct achieves approximately 34.4 tokens per second decode speed with a time-to-first-token of 5627ms using Q4_K_M quantization.
For coding workloads, Qwen3-VL 30B A3B Instruct on MacBook Pro M1 Max 64GB receives a S grade with 34.4 tok/s and 208K context.
On MacBook Pro M1 Max 64GB, Qwen3-VL 30B A3B Instruct can safely use up to 208K tokens of context. The model's official context limit is 256K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-3-vl-30b-a3b-on-m1-max-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
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 |
Not always. MacBook Pro M1 Max 64GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.