Nous Dolphin 13B needs ~32.4 GB VRAM. RTX PRO 6000 Blackwell Workstation Edition 96GB has 96.0 GB. With Q5_K_M quantization, expect ~164 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
164.0 tok/s
TTFT
1180 ms
Safe context
16K
Memory
32.4 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 | 164.0 tok/s | 644 ms | 16K |
| Coding | B | Runs well | 164.0 tok/s | 1180 ms | 16K |
| Agentic Coding | A | Runs well | 164.0 tok/s | 1717 ms | 16K |
| Reasoning | B | Runs well | 164.0 tok/s | 1395 ms | 16K |
| RAG | A | Runs well | 164.0 tok/s | 2146 ms | 16K |
How Nous Dolphin 13B (13B 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 | 5.1 GB | Low | B60 |
Q3_K_S | 3 | 6.4 GB | Low | B60 |
NVFP4 | 4 | 7.3 GB | Medium | B60 |
Q4_K_M | 4 | 7.9 GB | Medium | B60 |
Q5_K_M | 5 | 9.4 GB | High | B60 |
Q6_K | 6 | 10.7 GB | High | B60 |
Q8_0 | 8 | 13.9 GB | Very High | B60 |
F16Best for your GPU | 16 | 26.7 GB | Maximum | B62 |
Copy-paste commands to run Nous Dolphin 13B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "nousresearch/Nous-Dolphin-13B" \
--hf-file "Nous-Dolphin-13B-Q5_K_M.gguf" \
-c 4096 -ngl 99Yes, RTX PRO 6000 Blackwell Workstation Edition 96GB can run Nous Dolphin 13B with a B grade (Runs well). Expected decode speed: 164.0 tok/s.
Nous Dolphin 13B (13B parameters) requires approximately 32.4 GB of memory with Q5_K_M quantization.
The recommended quantization for Nous Dolphin 13B is Q5_K_M, which balances quality and memory efficiency.
On RTX PRO 6000 Blackwell Workstation Edition 96GB, Nous Dolphin 13B achieves approximately 164.0 tokens per second decode speed with a time-to-first-token of 1180ms using Q5_K_M quantization.
For coding workloads, Nous Dolphin 13B on RTX PRO 6000 Blackwell Workstation Edition 96GB receives a B grade with 164.0 tok/s and 16K context.
On RTX PRO 6000 Blackwell Workstation Edition 96GB, Nous Dolphin 13B can safely use up to 16K tokens of context. The model's official context limit is 16K, 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/nous-dolphin-13b-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>
Preview: