Hermes 4.3 36B needs ~29.0 GB but RTX A4000 16GB only has 16.0 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
13.0 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
3.1 tok/s
TTFT
63111 ms
Safe context
4K
Memory
29.0 GB / 16.0 GB
Offload
40%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 29.0 GB, but this setup only exposes 16.0 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 | F | Too heavy | 3.6 tok/s | 29361 ms | 4K |
| Coding | F | Too heavy | 3.1 tok/s | 63111 ms | 4K |
| Agentic Coding | F | Too heavy | 2.3 tok/s | 122203 ms | 4K |
| Reasoning | F | Too heavy | 3.1 tok/s | 74586 ms | 4K |
| RAG | F | Too heavy | 2.3 tok/s | 152754 ms | 4K |
How Hermes 4.3 36B (36B params) fits at each quantization level on RTX A4000 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 14.0 GB | Low | F0 |
Q3_K_S | 3 | 17.6 GB | Low | F0 |
NVFP4 | 4 | 20.2 GB | Medium | F0 |
Q4_K_M | 4 | 22.0 GB | Medium | F0 |
Q5_K_M | 5 | 25.9 GB | High | F0 |
Q6_K | 6 | 29.5 GB | High | F0 |
Q8_0 | 8 | 38.5 GB | Very High | F0 |
F16 | 16 | 73.8 GB | Maximum | F0 |
升级选项
RTX 5090 32GB经济之选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.
~$1,999 MSRP
RTX PRO 4500 Blackwell 32GB最佳性价比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.
~$2,499 MSRP
RTX 5000 Ada 32GBNVIDIA 升级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.
~$4,000 MSRP
No, Hermes 4.3 36B requires more memory than RTX A4000 16GB provides.
Hermes 4.3 36B (36B parameters) requires approximately 29.0 GB of memory with Q4_K_M quantization.
The recommended quantization for Hermes 4.3 36B is Q4_K_M, which balances quality and memory efficiency.
On RTX A4000 16GB, Hermes 4.3 36B achieves approximately 3.1 tokens per second decode speed with a time-to-first-token of 63111ms using Q4_K_M quantization.
For coding workloads, Hermes 4.3 36B on RTX A4000 16GB receives a F grade with 3.1 tok/s and 4K context.
On RTX A4000 16GB, Hermes 4.3 36B can safely use up to 4K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-nousresearch--hermes-4-3-36b-gguf-on-a4000-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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