DeepSeek R1 Distill 14B needs ~15.9 GB VRAM. NVIDIA V100 32GB has 32.0 GB. With Q4_K_M quantization, expect ~76 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
76.3 tok/s
TTFT
2539 ms
Safe context
33K
Memory
15.9 GB / 32.0 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 | A | Runs well | 76.3 tok/s | 1385 ms | 33K |
| Coding | A | Runs well | 76.3 tok/s | 2539 ms | 33K |
| Agentic Coding | A | Runs well | 76.3 tok/s | 3693 ms | 33K |
| Reasoning | A | Runs well | 76.3 tok/s | 3000 ms | 33K |
| RAG | A | Runs well | 76.3 tok/s | 4616 ms | 33K |
How DeepSeek R1 Distill 14B (14B params) fits at each quantization level on NVIDIA V100 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | B68 |
Q3_K_S | 3 | 6.9 GB | Low | B69 |
NVFP4 | 4 |
Copy-paste commands to run DeepSeek R1 Distill 14B on your machine.
Run
ollama run deepseek-r1Your hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 30.5B | S | 91.2 tok/s | ||
| 27B | S | 39.5 tok/s |
Yes, NVIDIA V100 32GB can run DeepSeek R1 Distill 14B with a A grade (Runs well). Expected decode speed: 76.3 tok/s.
DeepSeek R1 Distill 14B (14B parameters) requires approximately 15.9 GB of memory with Q4_K_M quantization.
The recommended quantization for DeepSeek R1 Distill 14B is Q4_K_M, which balances quality and memory efficiency.
On NVIDIA V100 32GB, DeepSeek R1 Distill 14B achieves approximately 76.3 tokens per second decode speed with a time-to-first-token of 2539ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill 14B on NVIDIA V100 32GB receives a A grade with 76.3 tok/s and 33K context.
On NVIDIA V100 32GB, DeepSeek R1 Distill 14B can safely use up to 33K tokens of context. The model's official context limit is 33K, 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/deepseek-r1-distill-14b-on-v100-32gb" 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 |
| B69 |
Q4_K_M | 4 | 8.5 GB | Medium | B70 |
Q5_K_M | 5 | 10.1 GB | High | A70 |
Q6_K | 6 | 11.5 GB | High | A71 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | A73 |
F16 | 16 | 28.7 GB | Maximum | F0 |
| 27B | S | 39.7 tok/s |
| 35B | S | 76.6 tok/s |
| 30B | S | 94.3 tok/s |