DeepSeek R1 Distill Qwen 14B needs ~13.0 GB VRAM. RTX 5060 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~33 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
32.5 tok/s
TTFT
5952 ms
Safe context
45K
Memory
13.0 GB / 16.0 GB
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 32.5 tok/s | 3247 ms | 45K |
| Coding | C | Runs well | 32.5 tok/s | 5952 ms | 45K |
| Agentic Coding | C | Tight fit | 32.5 tok/s | 8658 ms | 45K |
| Reasoning | C | Runs well | 32.5 tok/s | 7035 ms | 45K |
| RAG | C | Tight fit | 32.5 tok/s | 10823 ms | 45K |
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on RTX 5060 Ti 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C49 |
Q3_K_S | 3 | 6.9 GB | Low | C51 |
NVFP4 | 4 | 7.8 GB | Medium | C52 |
Q4_K_M | 4 | 8.5 GB | Medium | C52 |
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 startUpgrade options
RTX 3090 24GBBudget pickRaises estimated decode speed by about 136%.
Adds memory headroom for longer context windows and future model growth.
~$1,499 MSRP
RTX 4090 24GBBest valueRaises estimated decode speed by about 176%.
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP
RTX 3090 Ti 24GBNVIDIA upgradeRaises estimated decode speed by about 158%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
Yes, RTX 5060 Ti 16GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs well). Expected decode speed: 32.5 tok/s.
DeepSeek R1 Distill Qwen 14B (14B parameters) requires approximately 13.0 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 RTX 5060 Ti 16GB, DeepSeek R1 Distill Qwen 14B achieves approximately 32.5 tokens per second decode speed with a time-to-first-token of 5952ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill Qwen 14B on RTX 5060 Ti 16GB receives a C grade with 32.5 tok/s and 45K context.
On RTX 5060 Ti 16GB, DeepSeek R1 Distill Qwen 14B can safely use up to 45K 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-rtx-5060-ti-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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