DeepSeek LLM 67B needs ~57.2 GB VRAM. RTX PRO 6000 Blackwell Workstation Edition 96GB has 96.0 GB. With Q4_K_M quantization, expect ~40 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
40.1 tok/s
TTFT
4834 ms
Safe context
4K
Memory
57.2 GB / 96.0 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 | B | Runs well | 40.1 tok/s | 2636 ms | 4K |
| Coding | B | Runs well | 40.1 tok/s | 4834 ms | 4K |
| Agentic Coding | B | Runs well | 40.1 tok/s | 7031 ms | 4K |
| Reasoning | B | Runs well | 40.1 tok/s | 5712 ms | 4K |
| RAG | B | Runs well | 40.1 tok/s | 8788 ms | 4K |
How DeepSeek LLM 67B (67B params) fits at each quantization level on RTX PRO 6000 Blackwell Workstation Edition 96GB (96.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 26.1 GB | Low | C52 |
Q3_K_S | 3 | 32.8 GB | Low | C53 |
NVFP4 | 4 | 37.5 GB | Medium | C54 |
Q4_K_M | 4 | 40.9 GB | Medium | B55 |
Q5_K_M | 5 | 48.2 GB | High | B57 |
Q6_K | 6 | 54.9 GB | High | B58 |
Q8_0Best for your GPU | 8 | 71.7 GB | Very High | B58 |
F16 | 16 | 137.4 GB | Maximum | F0 |
Copy-paste commands to run DeepSeek LLM 67B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "deepseek-ai/deepseek-llm-67b-chat" \
--hf-file "deepseek-llm-67b-chat-Q4_K_M.gguf" \
-c 4096 -ngl 99Upgrade options
Yes, RTX PRO 6000 Blackwell Workstation Edition 96GB can run DeepSeek LLM 67B with a B grade (Runs well). Expected decode speed: 40.1 tok/s.
DeepSeek LLM 67B (67B parameters) requires approximately 57.2 GB of memory with Q4_K_M quantization.
The recommended quantization for DeepSeek LLM 67B is Q4_K_M, which balances quality and memory efficiency.
On RTX PRO 6000 Blackwell Workstation Edition 96GB, DeepSeek LLM 67B achieves approximately 40.1 tokens per second decode speed with a time-to-first-token of 4834ms using Q4_K_M quantization.
For coding workloads, DeepSeek LLM 67B on RTX PRO 6000 Blackwell Workstation Edition 96GB receives a B grade with 40.1 tok/s and 4K context.
On RTX PRO 6000 Blackwell Workstation Edition 96GB, DeepSeek LLM 67B can safely use up to 4K tokens of context. The model's official context limit is 4K, 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-llm-67b-on-rtx-pro-6000-blackwell-96gb" 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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