Qwen 2.5 VL 7B needs ~8.6 GB VRAM. MacBook Pro M4 Pro 24GB has 17.3 GB. With Q4_K_M quantization, expect ~49 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
49.2 tok/s
TTFT
3937 ms
Safe context
33K
Memory
8.6 GB / 17.3 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 | A | Runs well | 49.2 tok/s | 2148 ms | 33K |
| Coding | A | Runs well | 49.2 tok/s | 3937 ms | 33K |
| Agentic Coding | A | Runs well | 49.2 tok/s | 5727 ms | 33K |
| Reasoning | A | Runs well | 49.2 tok/s | 4653 ms | 33K |
| RAG | A | Runs well | 49.2 tok/s | 7158 ms | 33K |
How Qwen 2.5 VL 7B (7B params) fits at each quantization level on MacBook Pro M4 Pro 24GB (17.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | A76 |
Q3_K_S | 3 | 3.4 GB | Low | A76 |
NVFP4 | 4 |
Copy-paste commands to run Qwen 2.5 VL 7B on your machine.
Run
lms load Qwen2.5-VL-7B-Instruct && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | S | 37.9 tok/s | |
 Magistral Small 2507 | 24B | A | 17.8 tok/s |
Yes, MacBook Pro M4 Pro 24GB can run Qwen 2.5 VL 7B with a A grade (Runs well). Expected decode speed: 49.2 tok/s.
Qwen 2.5 VL 7B (7B parameters) requires approximately 8.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 VL 7B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Pro 24GB, Qwen 2.5 VL 7B achieves approximately 49.2 tokens per second decode speed with a time-to-first-token of 3937ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 VL 7B on MacBook Pro M4 Pro 24GB receives a A grade with 49.2 tok/s and 33K context.
On MacBook Pro M4 Pro 24GB, Qwen 2.5 VL 7B can safely use up to 33K tokens of context. The model's official context limit is 33K, 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-2.5-vl-7b-on-m4-pro-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
3.9 GB |
| Medium |
| A77 |
Q4_K_M | 4 | 4.3 GB | Medium | A77 |
Q5_K_M | 5 | 5.0 GB | High | A78 |
Q6_K | 6 | 5.7 GB | High | A78 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | A80 |
F16 | 16 | 14.3 GB | Maximum | F0 |
| Devstral Small 2 24B Instruct | 24B | A | 17.8 tok/s |
| Qwen 3 14B | 14B | S | 23.4 tok/s |
| Qwen 3 8B | 8B | S | 42.6 tok/s |
Not always. MacBook Pro M4 Pro 24GB 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.