Can DeepSeek R1 671B run on NVIDIA H100 80GB?
NO — Won't Fit
DeepSeek R1 671B needs ~477.8 GB but NVIDIA H100 80GB only has 80.0 GB. Try a smaller quantization or lighter model.
Operating mode
Choose the run profile you care about
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
397.8 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
3.0 tok/s
TTFT
64602 ms
Safe context
4K
Memory
477.8 GB / 80.0 GB
Offload
80%
Memory breakdown
See how fast it feels
With memory offload — actual speed may be lowerWhat limits this setup
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 477.8 GB, but this setup only exposes 80.0 GB of usable VRAM.
Best improvement path
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | F | Too heavy | 3.0 tok/s | 35237 ms | 4K |
| Coding | F | Too heavy | 3.0 tok/s | 64602 ms | 4K |
| Agentic Coding | F | Too heavy | 3.0 tok/s | 93966 ms | 4K |
| Reasoning | F | Too heavy | 3.0 tok/s | 76347 ms | 4K |
| RAG | F | Too heavy | 3.0 tok/s | 117458 ms | 4K |
Quantization options
How DeepSeek R1 671B (671B params) fits at each quantization level on NVIDIA H100 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 261.7 GB | Low | F0 |
Q3_K_S | 3 | 328.8 GB | Low | F0 |
NVFP4 | 4 | 375.8 GB | Medium | F0 |
Q4_K_M | 4 | 409.3 GB | Medium | F0 |
Q5_K_M | 5 | 483.1 GB | High | F0 |
Q6_K | 6 | 550.2 GB | High | F0 |
Q8_0 | 8 | 718.0 GB | Very High | F0 |
F16 | 16 | 1375.6 GB | Maximum | F0 |
