Nous Hermes 1.0 needs ~21.8 GB VRAM. Radeon Pro W7800 32GB has 32.0 GB. With Q4_K_M quantization, expect ~62 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
61.9 tok/s
TTFT
3128 ms
Safe context
16K
Memory
21.8 GB / 32.0 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 | 61.9 tok/s | 1706 ms | 16K |
| Coding | A | Runs well | 61.9 tok/s | 3128 ms | 16K |
| Agentic Coding | B | Runs with offload (needs ~0.3 GB host RAM) | 40.9 tok/s | 6893 ms | 16K |
| Reasoning | A | Runs well | 61.9 tok/s | 3696 ms | 16K |
| RAG | B | Runs with offload (needs ~0.3 GB host RAM) | 40.9 tok/s | 8616 ms |
How Nous Hermes 1.0 (9B params) fits at each quantization level on Radeon Pro W7800 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B64 |
Q3_K_S | 3 | 4.4 GB | Low | B64 |
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 | 51.4 tok/s | |
| Qwen 3.5 27B | 27B | S | 22.3 tok/s |
Yes, Radeon Pro W7800 32GB can run Nous Hermes 1.0 with a A grade (Runs well). Expected decode speed: 61.9 tok/s.
Nous Hermes 1.0 (9B parameters) requires approximately 21.8 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 Radeon Pro W7800 32GB, Nous Hermes 1.0 achieves approximately 61.9 tokens per second decode speed with a time-to-first-token of 3128ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on Radeon Pro W7800 32GB receives a A grade with 61.9 tok/s and 16K context.
On Radeon Pro W7800 32GB, 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-radeon-pro-w7800-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 16K |
5.0 GB |
| Medium |
| B64 |
Q4_K_M | 4 | 5.5 GB | Medium | B64 |
Q5_K_M | 5 | 6.5 GB | High | B65 |
Q6_K | 6 | 7.4 GB | High | B65 |
Q8_0 | 8 | 9.6 GB | Very High | B66 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | B70 |
| Qwen 3.6 27B | 27B | S | 16.9 tok/s |
| Qwen 3.6 35B A3B | 35B | S | 43.2 tok/s |
| Qwen3-VL 30B A3B Instruct | 30B | S | 53.1 tok/s |