Qwen 3 14B needs ~14.5 GB VRAM. MacBook Pro M4 Pro 24GB has 17.3 GB. With Q4_K_M quantization, expect ~23 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
Tight fit
Decode
23.4 tok/s
TTFT
8276 ms
Safe context
34K
Memory
14.5 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 | S | Runs well | 23.4 tok/s | 4514 ms | 34K |
| Coding | S | Tight fit | 23.4 tok/s | 8276 ms | 34K |
| Agentic Coding | S | Runs with offload | 23.4 tok/s | 12037 ms | 34K |
| Reasoning | S | Tight fit | 23.4 tok/s | 9780 ms | 34K |
| RAG | S | Runs with offload | 23.4 tok/s | 15047 ms | 34K |
How Qwen 3 14B (14B params) fits at each quantization level on MacBook Pro M4 Pro 24GB (17.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | S89 |
Q3_K_S | 3 | 6.9 GB | Low | S91 |
NVFP4 | 4 |
Copy-paste commands to run Qwen 3 14B on your machine.
Run
ollama run qwen3Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Magistral Small 2507 | 24B | A | 17.8 tok/s | |
| Devstral Small 2 24B Instruct | 24B | A | 17.8 tok/s |
Yes, MacBook Pro M4 Pro 24GB can run Qwen 3 14B with a S grade (Tight fit). Expected decode speed: 23.4 tok/s.
Qwen 3 14B (14B parameters) requires approximately 14.5 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen 3 14B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Pro 24GB, Qwen 3 14B achieves approximately 23.4 tokens per second decode speed with a time-to-first-token of 8276ms using Q4_K_M quantization.
For coding workloads, Qwen 3 14B on MacBook Pro M4 Pro 24GB receives a S grade with 23.4 tok/s and 34K context.
On MacBook Pro M4 Pro 24GB, Qwen 3 14B can safely use up to 34K tokens of context. The model's official context limit is 131K, 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-3-14b-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:
7.8 GB |
| Medium |
| S91 |
Q4_K_M | 4 | 8.5 GB | Medium | S92 |
Q5_K_M | 5 | 10.1 GB | High | S92 |
Q6_KBest for your GPU | 6 | 11.5 GB | High | S91 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
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.