Hermes 4.3 36B needs ~28.2 GB but RTX 3060 Ti 8GB only has 8.0 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
20.2 GB over capacity — needs offload or smaller quantization
Fit status
Too heavy
Decode
2.1 tok/s
TTFT
93038 ms
Safe context
4K
Memory
28.2 GB / 8.0 GB
Offload
70%
Usable VRAM is the main blocker for this model.
Not enough usable memory
The model needs 28.2 GB, but this setup only exposes 8.0 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 | 2.1 tok/s | 50748 ms | 4K |
| Coding | F | Too heavy | 2.1 tok/s | 93038 ms | 4K |
| Agentic Coding | F | Too heavy | 2.1 tok/s | 135328 ms | 4K |
| Reasoning | F | Too heavy | 2.1 tok/s | 109954 ms | 4K |
| RAG | F | Too heavy | 2.1 tok/s | 169160 ms | 4K |
How Hermes 4.3 36B (36B params) fits at each quantization level on RTX 3060 Ti 8GB (8.0 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 |
アップグレードオプション
RTX 5090 32GBコスパ重視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コスパ最良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アップグレード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 3060 Ti 8GB provides.
Hermes 4.3 36B (36B parameters) requires approximately 28.2 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 3060 Ti 8GB, Hermes 4.3 36B achieves approximately 2.1 tokens per second decode speed with a time-to-first-token of 93038ms using Q4_K_M quantization.
For coding workloads, Hermes 4.3 36B on RTX 3060 Ti 8GB receives a F grade with 2.1 tok/s and 4K context.
On RTX 3060 Ti 8GB, 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-rtx-3060-ti-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
