Intel Arc Pro B60 24GBBest value456 GB/s (+256)
B
Raises estimated decode speed by about 90%.31.1 tok/s decode
Raises estimated decode speed by about 90%.
~$599 MSRP
Qwen 2.5 Coder 14B needs ~15.8 GB VRAM. MacBook Pro M1 Pro 32GB has 23.0 GB. With Q4_K_M quantization, expect ~16 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
16.4 tok/s
TTFT
11776 ms
Safe context
55K
Memory
15.8 GB / 23.0 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 | B | Runs well | 16.4 tok/s | 6423 ms | 55K |
| Coding | B | Runs well | 16.4 tok/s | 11776 ms | 55K |
| Agentic Coding | B | Runs well | 16.4 tok/s | 17129 ms | 55K |
| Reasoning | B | Runs well | 16.4 tok/s | 13917 ms | 55K |
| RAG | B | Runs well | 16.4 tok/s | 21411 ms | 55K |
How Qwen 2.5 Coder 14B (14B params) fits at each quantization level on MacBook Pro M1 Pro 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | B60 |
Q3_K_S | 3 | 6.9 GB | Low | B61 |
NVFP4 | 4 | 7.8 GB | Medium | B62 |
Q4_K_M | 4 | 8.5 GB | Medium | B62 |
Q5_K_M | 5 | 10.1 GB | High | B63 |
Q6_K | 6 | 11.5 GB | High | B64 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | B64 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Copy-paste commands to run Qwen 2.5 Coder 14B on your machine.
Run
ollama run qwen2.5-coder:14bUpgrade options
Intel Arc Pro B60 24GBBest valueRaises estimated decode speed by about 90%.
~$599 MSRP
Raises estimated decode speed by about 99%.
~$2,499 MSRP
Yes, MacBook Pro M1 Pro 32GB can run Qwen 2.5 Coder 14B with a B grade (Runs well). Expected decode speed: 16.4 tok/s.
Qwen 2.5 Coder 14B (14B parameters) requires approximately 15.8 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 2.5 Coder 14B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M1 Pro 32GB, Qwen 2.5 Coder 14B achieves approximately 16.4 tokens per second decode speed with a time-to-first-token of 11776ms using Q4_K_M quantization.
For coding workloads, Qwen 2.5 Coder 14B on MacBook Pro M1 Pro 32GB receives a B grade with 16.4 tok/s and 55K context.
On MacBook Pro M1 Pro 32GB, Qwen 2.5 Coder 14B can safely use up to 55K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.
Not always. MacBook Pro M1 Pro 32GB 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/qwen-2.5-coder-14b-on-m1-pro-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: