DeepSeek R1 Distill Qwen 14B needs ~13.8 GB VRAM. NVIDIA L4 24GB has 24.0 GB. With Q4_K_M quantization, expect ~23 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
22.8 tok/s
TTFT
8479 ms
Safe context
116K
Memory
13.8 GB / 24.0 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 | 22.8 tok/s | 4625 ms | 116K |
| Coding | C | Runs well | 22.8 tok/s | 8479 ms | 116K |
| Agentic Coding | C | Runs well | 22.8 tok/s | 12333 ms | 116K |
| Reasoning | C | Runs well | 22.8 tok/s | 10020 ms | 116K |
| RAG | C | Runs well | 22.8 tok/s | 15416 ms | 116K |
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on NVIDIA L4 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C46 |
Q3_K_S | 3 | 6.9 GB | Low | C47 |
NVFP4 | 4 | 7.8 GB | Medium | C47 |
Q4_K_M | 4 | 8.5 GB | Medium | C48 |
Q5_K_M | 5 | 10.1 GB | High | C49 |
Q6_K | 6 | 11.5 GB | High | C50 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | C50 |
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 5090 32GBBudget pickRaises estimated decode speed by about 517%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
RTX PRO 4500 Blackwell 32GBBest valueRaises estimated decode speed by about 286%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
RTX 5000 Ada 32GBNVIDIA upgradeRaises estimated decode speed by about 137%.
Adds memory headroom for longer context windows and future model growth.
~$4,000 MSRP
Yes, NVIDIA L4 24GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs well). Expected decode speed: 22.8 tok/s.
DeepSeek R1 Distill Qwen 14B (14B parameters) requires approximately 13.8 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 NVIDIA L4 24GB, DeepSeek R1 Distill Qwen 14B achieves approximately 22.8 tokens per second decode speed with a time-to-first-token of 8479ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill Qwen 14B on NVIDIA L4 24GB receives a C grade with 22.8 tok/s and 116K context.
On NVIDIA L4 24GB, DeepSeek R1 Distill Qwen 14B can safely use up to 116K 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-l4-24gb" 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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