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
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VOOZH | about |
Hermes 4.3 36B needs ~29.0 GB but RTX 4090 Laptop 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
4.5 tok/s
TTFT
42951 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 | 5.3 tok/s | 19982 ms | 4K |
| Coding | F | Too heavy | 4.5 tok/s | 42951 ms | 4K |
| Agentic Coding | F | Too heavy | 3.4 tok/s | 83166 ms | 4K |
| Reasoning | F | Too heavy | 4.5 tok/s | 50760 ms | 4K |
| RAG | F | Too heavy | 3.4 tok/s | 103957 ms | 4K |
How Hermes 4.3 36B (36B params) fits at each quantization level on RTX 4090 Laptop 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 |
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.
~$1,999 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.
~$2,499 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.
~$4,000 MSRP