Nous Dolphin 13B needs ~42.0 GB VRAM. NVIDIA GB200 192GB has 192.0 GB. With Q5_K_M quantization, expect ~182 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
182.0 tok/s
TTFT
1064 ms
Safe context
16K
Memory
42.0 GB / 192.0 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 | 182.0 tok/s | 580 ms | 16K |
| Coding | B | Runs well | 182.0 tok/s | 1064 ms | 16K |
| Agentic Coding | B | Runs well | 182.0 tok/s | 1547 ms | 16K |
| Reasoning | B | Runs well | 182.0 tok/s | 1257 ms | 16K |
| RAG | B | Runs well | 182.0 tok/s | 1934 ms | 16K |
How Nous Dolphin 13B (13B params) fits at each quantization level on NVIDIA GB200 192GB (192.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.1 GB | Low | B58 |
Q3_K_S | 3 | 6.4 GB | Low | B58 |
NVFP4 | 4 | 7.3 GB | Medium | B58 |
Q4_K_M | 4 | 7.9 GB | Medium | B58 |
Q5_K_M | 5 | 9.4 GB | High | B58 |
Q6_K | 6 | 10.7 GB | High | B58 |
Q8_0 | 8 | 13.9 GB | Very High | B58 |
F16Best for your GPU | 16 | 26.7 GB | Maximum | B59 |
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, NVIDIA GB200 192GB can run Nous Dolphin 13B with a B grade (Runs well). Expected decode speed: 182.0 tok/s.
Nous Dolphin 13B (13B parameters) requires approximately 42.0 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 NVIDIA GB200 192GB, Nous Dolphin 13B achieves approximately 182.0 tokens per second decode speed with a time-to-first-token of 1064ms using Q5_K_M quantization.
For coding workloads, Nous Dolphin 13B on NVIDIA GB200 192GB receives a B grade with 182.0 tok/s and 16K context.
On NVIDIA GB200 192GB, 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-gb200-192gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: