DeepSeek R1 Distill Qwen 14B needs ~13.7 GB VRAM. MacBook Air M4 24GB has 17.3 GB. With Q4_K_M quantization, expect ~9 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
8.9 tok/s
TTFT
21745 ms
Safe context
51K
Memory
13.7 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 | C | Runs well | 8.9 tok/s | 11861 ms | 51K |
| Coding | C | Runs well | 8.9 tok/s | 21745 ms | 51K |
| Agentic Coding | C | Tight fit | 8.9 tok/s | 31630 ms | 51K |
| Reasoning | C | Runs well | 8.9 tok/s | 25699 ms | 51K |
| RAG | C | Tight fit | 8.9 tok/s | 39537 ms | 51K |
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on MacBook Air M4 24GB (17.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C49 |
Q3_K_S | 3 | 6.9 GB | Low | C50 |
NVFP4 | 4 | 7.8 GB | Medium | C51 |
Q4_K_M | 4 | 8.5 GB | Medium | C51 |
Q5_K_M | 5 | 10.1 GB | High | C51 |
Q6_KBest for your GPU | 6 | 11.5 GB | High | C51 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
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 startOpções de upgrade
Raises estimated decode speed by about 206%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
Raises estimated decode speed by about 84%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
Raises estimated decode speed by about 71%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
Yes, MacBook Air M4 24GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs well). Expected decode speed: 8.9 tok/s.
DeepSeek R1 Distill Qwen 14B (14B parameters) requires approximately 13.7 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 Air M4 24GB, DeepSeek R1 Distill Qwen 14B achieves approximately 8.9 tokens per second decode speed with a time-to-first-token of 21745ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill Qwen 14B on MacBook Air M4 24GB receives a C grade with 8.9 tok/s and 51K context.
On MacBook Air M4 24GB, DeepSeek R1 Distill Qwen 14B can safely use up to 51K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. MacBook Air M4 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.
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-air-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: