Nous Hermes 1.0 needs ~21.3 GB VRAM. Quadro RTX 6000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~85 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
Tight fit
Decode
84.5 tok/s
TTFT
2292 ms
Safe context
16K
Memory
21.3 GB / 24.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 84.5 tok/s | 1250 ms | 16K |
| Coding | A | Tight fit | 84.5 tok/s | 2292 ms | 16K |
| Agentic Coding | F | Too heavy | 29.6 tok/s | 9510 ms | 16K |
| Reasoning | A | Tight fit | 84.5 tok/s | 2709 ms | 16K |
| RAG | F | Too heavy | 29.6 tok/s | 11888 ms | 16K |
How Nous Hermes 1.0 (9B params) fits at each quantization level on Quadro RTX 6000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B65 |
Q3_K_S | 3 | 4.4 GB | Low | B66 |
NVFP4 | 4 | 5.0 GB | Medium | B66 |
Q4_K_M | 4 | 5.5 GB | Medium | B66 |
Q5_K_M | 5 | 6.5 GB | High | B67 |
Q6_K | 6 | 7.4 GB | High | B67 |
Q8_0 | 8 | 9.6 GB | Very High | B69 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | A70 |
Copy-paste commands to run Nous Hermes 1.0 on your machine.
Run
lms load Nous-Hermes-1.0 && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 70.1 tok/s | |
| Qwen 3.5 27B | 27B | S | 30.4 tok/s | |
| Qwen 3.6 27B | 27B | S | 30.5 tok/s | |
| Qwen3-VL 30B A3B Instruct | 30B | S | 72.5 tok/s | |
| Qwen 3.5 35B A3B | 35B | A | 37.9 tok/s |
Yes, Quadro RTX 6000 24GB can run Nous Hermes 1.0 with a A grade (Tight fit). Expected decode speed: 84.5 tok/s.
Nous Hermes 1.0 (9B parameters) requires approximately 21.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Nous Hermes 1.0 is Q4_K_M, which balances quality and memory efficiency.
On Quadro RTX 6000 24GB, Nous Hermes 1.0 achieves approximately 84.5 tokens per second decode speed with a time-to-first-token of 2292ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on Quadro RTX 6000 24GB receives a A grade with 84.5 tok/s and 16K context.
On Quadro RTX 6000 24GB, Nous Hermes 1.0 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-hermes-1.0-on-quadro-rtx-6000-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: