Qwen 2.5 VL 7B needs ~12.9 GB VRAM. Mac mini M4 64GB has 46.1 GB. With Q4_K_M quantization, expect ~20 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
20.2 tok/s
TTFT
9579 ms
Safe context
33K
Memory
12.9 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 | A | Runs well | 20.2 tok/s | 5225 ms | 33K |
| Coding | A | Runs well | 20.2 tok/s | 9579 ms | 33K |
| Agentic Coding | A | Runs well | 20.2 tok/s | 13933 ms | 33K |
| Reasoning | A | Runs well | 20.2 tok/s | 11321 ms | 33K |
| RAG | A | Runs well | 20.2 tok/s | 17416 ms | 33K |
How Qwen 2.5 VL 7B (7B params) fits at each quantization level on Mac mini M4 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | A71 |
Q3_K_S | 3 | 3.4 GB | Low | A71 |
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 |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 13.1 tok/s | |
| Qwen 3.5 27B | 27B | S | 9.3 tok/s |
Yes, Mac mini M4 64GB can run Qwen 2.5 VL 7B with a A grade (Runs well). Expected decode speed: 20.2 tok/s.
Qwen 2.5 VL 7B (7B parameters) requires approximately 12.9 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 Mac mini M4 64GB, Qwen 2.5 VL 7B achieves approximately 20.2 tokens per second decode speed with a time-to-first-token of 9579ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 VL 7B on Mac mini M4 64GB receives a A grade with 20.2 tok/s and 33K context.
On Mac mini M4 64GB, 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-mini-64gb" 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 |
| A71 |
Q4_K_M | 4 | 4.3 GB | Medium | A71 |
Q5_K_M | 5 | 5.0 GB | High | A71 |
Q6_K | 6 | 5.7 GB | High | A72 |
Q8_0 | 8 | 7.5 GB | Very High | A72 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | A74 |
| Qwen 3.6 27B | 27B | S | 7.1 tok/s |
| Qwen 3.6 35B A3B | 35B | S | 12.1 tok/s |
| Qwen3-VL 30B A3B Instruct | 30B | S | 13.5 tok/s |
Not always. Mac mini M4 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.