DeepSeek R1 Distill Qwen 14B needs ~16.3 GB VRAM. MacBook Pro M4 Pro 48GB has 34.6 GB. With Q4_K_M quantization, expect ~22 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
21.7 tok/s
TTFT
8938 ms
Safe context
194K
Memory
16.3 GB / 34.6 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 | C | Runs well | 21.7 tok/s | 4875 ms | 194K |
| Coding | C | Runs well | 21.7 tok/s | 8938 ms | 194K |
| Agentic Coding | C | Runs well | 21.7 tok/s | 13000 ms | 194K |
| Reasoning | C | Runs well | 21.7 tok/s | 10563 ms | 194K |
| RAG | C | Runs well | 21.7 tok/s | 16250 ms | 194K |
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on MacBook Pro M4 Pro 48GB (34.6 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C44 |
Q3_K_S | 3 | 6.9 GB | Low | C44 |
NVFP4 | 4 |
Copy-paste commands to run DeepSeek R1 Distill Qwen 14B on your machine.
Run
lms load hf-unsloth--deepseek-r1-distill-qwen-14b-gguf && lms server startUpgrade options
Raises estimated decode speed by about 150%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 137%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 200%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, MacBook Pro M4 Pro 48GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs well). Expected decode speed: 21.7 tok/s.
DeepSeek R1 Distill Qwen 14B (14B parameters) requires approximately 16.3 GB of memory with Q4_K_M quantization.
The recommended quantization for DeepSeek R1 Distill Qwen 14B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Pro 48GB, DeepSeek R1 Distill Qwen 14B achieves approximately 21.7 tokens per second decode speed with a time-to-first-token of 8938ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill Qwen 14B on MacBook Pro M4 Pro 48GB receives a C grade with 21.7 tok/s and 194K context.
On MacBook Pro M4 Pro 48GB, DeepSeek R1 Distill Qwen 14B can safely use up to 194K tokens of context. The model's official context limit is —, 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/hf-unsloth--deepseek-r1-distill-qwen-14b-gguf-on-m4-pro-48gb" 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 |
| C44 |
Q4_K_M | 4 | 8.5 GB | Medium | C45 |
Q5_K_M | 5 | 10.1 GB | High | C45 |
Q6_K | 6 | 11.5 GB | High | C46 |
Q8_0 | 8 | 15.0 GB | Very High | C47 |
F16Best for your GPU | 16 | 28.7 GB | Maximum | C48 |
Not always. MacBook Pro M4 Pro 48GB 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.