Nous Hermes 1.0 needs ~20.1 GB but RTX A2000 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
8.1 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
10.4 tok/s
TTFT
18679 ms
Safe context
5K
Memory
20.1 GB / 12.0 GB
Offload
40%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 20.1 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 (needs ~0.8 GB host RAM) | 22.2 tok/s | 4755 ms | 5K |
| Coding | F | Too heavy | 10.4 tok/s | 18679 ms | 5K |
| Agentic Coding | F | Too heavy | 6.1 tok/s | 45880 ms | 5K |
| Reasoning | F | Too heavy | 10.4 tok/s | 22075 ms | 5K |
| RAG | F | Too heavy | 6.1 tok/s | 57350 ms | 5K |
How Nous Hermes 1.0 (9B params) fits at each quantization level on RTX A2000 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
RTX 4000 Ada 20GBBudget pickMakes 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.
~$1,250 MSRP
RTX 3090 24GBBest valueMakes 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.
~$1,499 MSRP
RTX 4090 24GBNVIDIA upgradeMakes 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.
~$1,599 MSRP
No, Nous Hermes 1.0 requires more memory than RTX A2000 12GB provides.
Nous Hermes 1.0 (9B parameters) requires approximately 20.1 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 A2000 12GB, Nous Hermes 1.0 achieves approximately 10.4 tokens per second decode speed with a time-to-first-token of 18679ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on RTX A2000 12GB receives a F grade with 10.4 tok/s and 5K context.
On RTX A2000 12GB, Nous Hermes 1.0 can safely use up to 5K 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-a2000-12gb" 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.
