Can Qwen 2.5 VL 72B run on MacBook Pro M3 Max 128GB?
YES — Runs Great
Qwen 2.5 VL 72B needs ~63.5 GB VRAM. MacBook Pro M3 Max 128GB has 92.2 GB. With Q4_K_M quantization, expect ~6 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
5.9 tok/s
TTFT
32578 ms
Safe context
33K
Memory
63.5 GB / 92.2 GB
Memory breakdown
See how fast it feels
What limits this setup
The model fits in shared memory, but shared-memory bandwidth is now the real limiter.
Fit does not mean dedicated-VRAM speed
Unified or shared memory can make a model technically fit, but sustained tokens per second may still trail a discrete high-bandwidth GPU with less total memory.
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
Prioritize bandwidth, not only capacity
If this workload feels slow, the next useful step is often a GPU tier with materially faster memory bandwidth rather than only a small bump in capacity.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Runs well | 5.9 tok/s | 17770 ms | 33K |
| Coding | S | Runs well | 5.9 tok/s | 32578 ms | 33K |
| Agentic Coding | S | Runs well | 5.9 tok/s | 47386 ms | 33K |
| Reasoning | S | Runs well | 5.9 tok/s | 38502 ms | 33K |
| RAG | S | Runs well | 5.9 tok/s | 59233 ms | 33K |
Quantization options
How Qwen 2.5 VL 72B (72B params) fits at each quantization level on MacBook Pro M3 Max 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 28.1 GB | Low | A83 |
Q3_K_S | 3 | 35.3 GB | Low | A85 |
NVFP4 | 4 | 40.3 GB | Medium | S86 |
Q4_K_M | 4 | 43.9 GB | Medium | S87 |
Q5_K_M | 5 | 51.8 GB | High | S88 |
Q6_K | 6 | 59.0 GB | High | S88 |
Q8_0Best for your GPU | 8 | 77.0 GB | Very High | S88 |
F16 | 16 | 147.6 GB | Maximum | F0 |
Get started
Copy-paste commands to run Qwen 2.5 VL 72B on your machine.
Run
lms load Qwen2.5-VL-72B-Instruct && lms server startYour hardware
More models your MacBook Pro M3 Max 128GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Devstral 2 123B Instruct | 123B | S | 3.3 tok/s | |
 Qwen 3.5 122B A10B | 122B | S | 15 tok/s | |
| Mistral Small 4 119B | 119B | S | 16 tok/s | |
 GPT-OSS 120B | 117B | A | 3.7 tok/s | |
 Command A 111B | 111B | A | 3.9 tok/s |
Frequently asked questions
Can MacBook Pro M3 Max 128GB run Qwen 2.5 VL 72B?
Yes, MacBook Pro M3 Max 128GB can run Qwen 2.5 VL 72B with a S grade (Runs well). Expected decode speed: 5.9 tok/s.
How much VRAM does Qwen 2.5 VL 72B need?
Qwen 2.5 VL 72B (72B parameters) requires approximately 63.5 GB of memory with Q4_K_M quantization.
What is the best quantization for Qwen 2.5 VL 72B?
The recommended quantization for Qwen 2.5 VL 72B is Q4_K_M, which balances quality and memory efficiency.
What speed will Qwen 2.5 VL 72B run at on MacBook Pro M3 Max 128GB?
On MacBook Pro M3 Max 128GB, Qwen 2.5 VL 72B achieves approximately 5.9 tokens per second decode speed with a time-to-first-token of 32578ms using Q4_K_M quantization.
Can MacBook Pro M3 Max 128GB run Qwen 2.5 VL 72B for coding?
For coding workloads, Qwen 2.5 VL 72B on MacBook Pro M3 Max 128GB receives a S grade with 5.9 tok/s and 33K context.
What context window can Qwen 2.5 VL 72B use on MacBook Pro M3 Max 128GB?
On MacBook Pro M3 Max 128GB, Qwen 2.5 VL 72B can safely use up to 33K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.
What should I upgrade first if Qwen 2.5 VL 72B feels slow on MacBook Pro M3 Max 128GB?
Prioritize bandwidth, not only capacity. If this workload feels slow, the next useful step is often a GPU tier with materially faster memory bandwidth rather than only a small bump in capacity.
Is unified memory on MacBook Pro M3 Max 128GB as fast as VRAM for Qwen 2.5 VL 72B?
Not always. MacBook Pro M3 Max 128GB 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.
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