Nous Hermes 1.0 needs ~21.3 GB VRAM. NVIDIA A30 24GB has 24.0 GB. With Q4_K_M quantization, expect ~126 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
126.0 tok/s
TTFT
1537 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 | 126.0 tok/s | 838 ms | 16K |
| Coding | A | Tight fit | 126.0 tok/s | 1537 ms | 16K |
| Agentic Coding | F | Too heavy | 49.3 tok/s | 5717 ms | 16K |
| Reasoning | A | Tight fit | 126.0 tok/s | 1816 ms | 16K |
| RAG | F | Too heavy | 49.3 tok/s | 7146 ms | 16K |
How Nous Hermes 1.0 (9B params) fits at each quantization level on NVIDIA A30 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 | 110 tok/s | |
| Qwen 3.5 27B | 27B | S | 47.7 tok/s |
Yes, NVIDIA A30 24GB can run Nous Hermes 1.0 with a A grade (Tight fit). Expected decode speed: 126.0 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 NVIDIA A30 24GB, Nous Hermes 1.0 achieves approximately 126.0 tokens per second decode speed with a time-to-first-token of 1537ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on NVIDIA A30 24GB receives a A grade with 126.0 tok/s and 16K context.
On NVIDIA A30 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-a30-24gb" 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 | 47.9 tok/s |
| Qwen3-VL 30B A3B Instruct | 30B | S | 113.8 tok/s |
| Qwen 3.5 35B A3B | 35B | A | 61.6 tok/s |