DeepSeek R1 Distill Qwen 14B needs ~13.0 GB VRAM. RTX A4000 16GB has 16.0 GB. With Q4_K_M quantization, expect ~37 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
36.7 tok/s
TTFT
5272 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 | 36.7 tok/s | 2876 ms | 45K |
| Coding | C | Runs well | 36.7 tok/s | 5272 ms | 45K |
| Agentic Coding | C | Tight fit | 36.7 tok/s | 7669 ms | 45K |
| Reasoning | C | Runs well | 36.7 tok/s | 6231 ms | 45K |
| RAG | C | Tight fit | 36.7 tok/s | 9586 ms | 45K |
Inference speed
Estimated decode speed (tokens/sec) for DeepSeek R1 Distill Qwen 14B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~141 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 140.6 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 89.7 | Fits |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 80.9 | Fits |
| RTX 3090 24GB | 24 GB | Q4_K_M | 76.7 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 75.1 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 65.2 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 54.3 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 51.5 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 35.4 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 35.4 | Fits |
| RTX 4070 12GB | 12 GB | Q4_K_M | 33.2 | Offloads |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 28.1 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 25.8 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 21.7 | Fits |
| RTX 3060 12GB | 12 GB | Q4_K_M | 19.5 | Offloads |
| RTX 4060 8GB | 8 GB | Q4_K_M | 7.2 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on RTX A4000 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 4090 24GBBudget pickRaises estimated decode speed by about 144%.
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP
RTX 3090 Ti 24GBNVIDIA upgradeRaises estimated decode speed by about 128%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
RTX A4500 20GBBest valueRaises estimated decode speed by about 59%.
Adds memory headroom for longer context windows and future model growth.
~$2,000 MSRP
Yes, RTX A4000 16GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs well). Expected decode speed: 36.7 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 A4000 16GB, DeepSeek R1 Distill Qwen 14B achieves approximately 36.7 tokens per second decode speed with a time-to-first-token of 5272ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill Qwen 14B on RTX A4000 16GB receives a C grade with 36.7 tok/s and 45K context.
On RTX A4000 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-a4000-16gb" 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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