Nous Hermes 1.0 needs ~19.8 GB but RX 7700 XT 12GB only has 12.0 GB. Try a smaller quantization or lighter model.
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
7.8 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
12.3 tok/s
TTFT
15684 ms
Safe context
6K
Memory
19.8 GB / 12.0 GB
Offload
40%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 19.8 GB, but this setup only exposes 12.0 GB of usable VRAM.
Add more VRAM headroom
The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Very compromised | 26.8 tok/s | 3938 ms | 6K |
| Coding | F | Too heavy | 12.3 tok/s | 15684 ms | 6K |
| Agentic Coding | F | Too heavy | 7.1 tok/s | 39763 ms | 6K |
| Reasoning | F | Too heavy | 12.3 tok/s | 18535 ms | 6K |
| RAG | F | Too heavy | 7.1 tok/s | 49704 ms | 6K |
How Nous Hermes 1.0 (9B params) fits at each quantization level on RX 7700 XT 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | A71 |
Q3_K_S | 3 | 4.4 GB | Low | A72 |
NVFP4 | 4 |
Upgrade options
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$899 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$999 MSRP
Makes the model fit on the accelerator instead of staying completely out of reach.
Removes host-memory offload, which is usually the single biggest latency and throughput win.
~$1,899 MSRP
No, Nous Hermes 1.0 requires more memory than RX 7700 XT 12GB provides.
Nous Hermes 1.0 (9B parameters) requires approximately 19.8 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 RX 7700 XT 12GB, Nous Hermes 1.0 achieves approximately 12.3 tokens per second decode speed with a time-to-first-token of 15684ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on RX 7700 XT 12GB receives a F grade with 12.3 tok/s and 6K context.
On RX 7700 XT 12GB, Nous Hermes 1.0 can safely use up to 6K 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-rx-7700-xt-12gb" 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 |
| A73 |
Q4_K_M | 4 | 5.5 GB | Medium | A73 |
Q5_K_M | 5 | 6.5 GB | High | A73 |
Q6_KBest for your GPU | 6 | 7.4 GB | High | A72 |
Q8_0 | 8 | 9.6 GB | Very High | F0 |
F16 | 16 | 18.5 GB | Maximum | F0 |
Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.
