RTX PRO 5000 Blackwell 48GBBudget pick1344 GB/s (+544)
C
Raises estimated decode speed by about 157%.132.2 tok/s decode
Raises estimated decode speed by about 157%.
~$4,999 MSRP
DeepSeek R1 Distill Qwen 14B needs ~18.0 GB VRAM. Mac Studio M1 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~52 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
51.5 tok/s
TTFT
3758 ms
Safe context
290K
Memory
18.0 GB / 46.1 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 | 51.5 tok/s | 2050 ms | 290K |
| Coding | C | Runs well | 51.5 tok/s | 3758 ms | 290K |
| Agentic Coding | C | Runs well | 51.5 tok/s | 5466 ms | 290K |
| Reasoning | C | Runs well | 51.5 tok/s | 4441 ms | 290K |
| RAG | C | Runs well | 51.5 tok/s | 6832 ms | 290K |
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on Mac Studio M1 Ultra 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C42 |
Q3_K_S | 3 | 6.9 GB | Low | C42 |
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
RTX PRO 5000 Blackwell 48GBBudget pickRaises estimated decode speed by about 157%.
~$4,999 MSRP
NVIDIA L40 48GBBest valueRaises estimated decode speed by about 61%.
~$5,500 MSRP
Yes, Mac Studio M1 Ultra 64GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs well). Expected decode speed: 51.5 tok/s.
DeepSeek R1 Distill Qwen 14B (14B parameters) requires approximately 18.0 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 Mac Studio M1 Ultra 64GB, DeepSeek R1 Distill Qwen 14B achieves approximately 51.5 tokens per second decode speed with a time-to-first-token of 3758ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill Qwen 14B on Mac Studio M1 Ultra 64GB receives a C grade with 51.5 tok/s and 290K context.
On Mac Studio M1 Ultra 64GB, DeepSeek R1 Distill Qwen 14B can safely use up to 290K 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-m1-ultra-64gb" 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 |
| C43 |
Q4_K_M | 4 | 8.5 GB | Medium | C43 |
Q5_K_M | 5 | 10.1 GB | High | C43 |
Q6_K | 6 | 11.5 GB | High | C44 |
Q8_0 | 8 | 15.0 GB | Very High | C45 |
F16Best for your GPU | 16 | 28.7 GB | Maximum | C48 |
Not always. Mac Studio M1 Ultra 64GB 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.