MacBook Pro M4 32GBBudget pick
32 GB Unified (+14)
C
Adds memory headroom for longer context windows and future model growth.8.9 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$799 MSRP
Can DeepSeek R1 Distill Qwen 14B run on MacBook Pro M3 Pro 18GB?
YES — With Offload
C48Usable
○Estimated from fit model
DeepSeek R1 Distill Qwen 14B needs ~13.0 GB VRAM. MacBook Pro M3 Pro 18GB has 13.0 GB. With Q4_K_M quantization, expect ~13 tok/s.
Runtime: llama.cppCapacity: OffloadBandwidth: Very lowStack: StandardBottleneck: Memory bandwidth
Share:
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 13.0 GB, 12.6 tok/s, Runs with offload (needs ~0 GB host RAM)
13.0 GB required13.0 GB available
100% VRAM used
Fit status
Runs with offload (needs ~0 GB host RAM)
Decode
12.6 tok/s
TTFT
15319 ms
Safe context
15K
Memory
13.0 GB / 13.0 GB
Memory breakdown
Weights8.5 GB
KV Cache1.6 GB
Runtime0.9 GB
Headroom1.9 GB
See how fast it feels
See how fast it feelsDeepSeek R1 Distill Qwen 14B on MacBook Pro M3 Pro 18GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 12.6 tok/s decode · 15.3s TTFT (warm) · 32 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
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.
Best improvement path
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Tight fit | 12.8 tok/s | 8236 ms | 15K |
| Coding | C | Runs with offload (needs ~0 GB host RAM) | 12.6 tok/s | 15319 ms | 15K |
| Agentic Coding | D | Very compromised (needs ~1 GB host RAM) | 10.5 tok/s | 26744 ms | 15K |
| Reasoning | C | Runs with offload (needs ~0 GB host RAM) | 12.6 tok/s | 18104 ms | 15K |
| RAG | D | Very compromised (needs ~1 GB host RAM) | 10.5 tok/s | 33431 ms | 15K |
Quantization options
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on MacBook Pro M3 Pro 18GB (13.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C52 |
Q3_K_S | 3 | 6.9 GB | Low | C52 |
NVFP4 | 4 | 7.8 GB | Medium | C52 |
Q4_K_MBest for your GPU | 4 | 8.5 GB | Medium | C52 |
Q5_K_M | 5 | 10.1 GB | High | F0 |
Q6_K | 6 | 11.5 GB | High | F0 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Get started
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
Hardware that runs DeepSeek R1 Distill Qwen 14B well
MacBook Air M4 24GBBest value
24 GB Unified (+6)
C
Adds memory headroom for longer context windows and future model growth.8.9 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$1,099 MSRP
MacBook Pro M3 24GBApple upgrade
24 GB Unified (+6)
C
Adds memory headroom for longer context windows and future model growth.8 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$1,099 MSRP
768 GB/s (+618)
B
Raises estimated decode speed by about 499%.75.5 tok/s decode
Raises estimated decode speed by about 499%.
Adds memory headroom for longer context windows and future model growth.