Nous Hermes 1.0 needs ~21.3 GB VRAM. RTX 3090 24GB has 24.0 GB. With Q4_K_M quantization, expect ~119 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
119.3 tok/s
TTFT
1622 ms
Safe context
16K
Memory
21.3 GB / 24.0 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 | A | Runs well | 119.3 tok/s | 885 ms | 16K |
| Coding | A | Tight fit | 119.3 tok/s | 1622 ms | 16K |
| Agentic Coding | F | Too heavy | 44.3 tok/s | 6350 ms | 16K |
| Reasoning | A | Tight fit | 119.3 tok/s | 1917 ms | 16K |
| RAG | F | Too heavy | 44.3 tok/s | 7937 ms | 16K |
How Nous Hermes 1.0 (9B params) fits at each quantization level on RTX 3090 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 |
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 | 99.1 tok/s | |
| Qwen 3.5 27B | 27B | S | 43 tok/s |
Yes, RTX 3090 24GB can run Nous Hermes 1.0 with a A grade (Tight fit). Expected decode speed: 119.3 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 RTX 3090 24GB, Nous Hermes 1.0 achieves approximately 119.3 tokens per second decode speed with a time-to-first-token of 1622ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on RTX 3090 24GB receives a A grade with 119.3 tok/s and 16K context.
On RTX 3090 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-rtx-3090-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
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 |
| Qwen 3.6 27B | 27B | S | 43.1 tok/s |
| Qwen3-VL 30B A3B Instruct | 30B | S | 102.5 tok/s |
| Qwen 3.5 35B A3B | 35B | A | 55.5 tok/s |