Adds memory headroom for longer context windows and future model growth.
〜$4,650 MSRP
Hermes 4.3 36B needs ~30.6 GB VRAM. NVIDIA V100 32GB has 32.0 GB. With Q4_K_M quantization, expect ~28 tok/s.
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
Fit status
Runs with offload
Decode
27.5 tok/s
TTFT
7051 ms
Safe context
21K
Memory
30.6 GB / 32.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Tight fit | 27.5 tok/s | 3846 ms | 21K |
| Coding | C | Runs with offload | 27.5 tok/s | 7051 ms | 21K |
| Agentic Coding | D | Very compromised (needs ~1.8 GB host RAM) | 20.4 tok/s | 13807 ms | 21K |
| Reasoning | C | Runs with offload | 27.5 tok/s | 8332 ms | 21K |
| RAG | D | Very compromised | 20.4 tok/s | 17258 ms | 21K |
How Hermes 4.3 36B (36B params) fits at each quantization level on NVIDIA V100 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 14.0 GB | Low | C48 |
Q3_K_S | 3 | 17.6 GB | Low | C49 |
NVFP4 | 4 | 20.2 GB | Medium | C49 |
Q4_K_MBest for your GPU | 4 | 22.0 GB | Medium | C49 |
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 |
Copy-paste commands to run Hermes 4.3 36B on your machine.
Run
lms load hf-nousresearch--hermes-4-3-36b-gguf && lms server startアップグレードオプション
Adds memory headroom for longer context windows and future model growth.
〜$4,650 MSRP
Raises estimated decode speed by about 87%.
Adds memory headroom for longer context windows and future model growth.
〜$4,999 MSRP
Adds memory headroom for longer context windows and future model growth.
〜$5,500 MSRP
Yes, NVIDIA V100 32GB can run Hermes 4.3 36B with a C grade (Runs with offload). Expected decode speed: 27.5 tok/s.
Hermes 4.3 36B (36B parameters) requires approximately 30.6 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 NVIDIA V100 32GB, Hermes 4.3 36B achieves approximately 27.5 tokens per second decode speed with a time-to-first-token of 7051ms using Q4_K_M quantization.
For coding workloads, Hermes 4.3 36B on NVIDIA V100 32GB receives a C grade with 27.5 tok/s and 21K context.
On NVIDIA V100 32GB, Hermes 4.3 36B can safely use up to 21K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
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-v100-32gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: