Mac Studio M3 Ultra 96GBBudget pick
96 GB Unified (+48)819 GB/s (+147)
C
Adds memory headroom for longer context windows and future model growth.65.2 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
NousResearch Hermes 4 14B needs ~16.2 GB VRAM. Quadro RTX 8000 48GB has 48.0 GB. With Q4_K_M quantization, expect ~54 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 well
Decode
54.3 tok/s
TTFT
3566 ms
Safe context
326K
Memory
16.2 GB / 48.0 GB
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 54.3 tok/s | 1945 ms | 326K |
| Coding | C | Runs well | 54.3 tok/s | 3566 ms | 326K |
| Agentic Coding | C | Runs well | 54.3 tok/s | 5186 ms | 326K |
| Reasoning | C | Runs well | 54.3 tok/s | 4214 ms | 326K |
| RAG | C | Runs well | 54.3 tok/s | 6483 ms | 326K |
Inference speed
Estimated decode speed (tokens/sec) for NousResearch Hermes 4 14B at Q4_K_M across popular GPUs and Apple Silicon, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~141 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.
| GPU / Mac | Memory | Quant | Speed (tok/s) | Fits? |
|---|---|---|---|---|
 RTX 5090 32GB | 32 GB | Q4_K_M | 140.6 | Fits |
| RTX 4090 24GB | 24 GB | Q4_K_M | 89.7 | Fits |
RX 7900 XTX 24GB | 24 GB | Q4_K_M | 80.9 | Fits |
| RTX 3090 24GB | 24 GB | Q4_K_M | 76.7 | Fits |
| RTX 4080 Super 16GB | 16 GB | Q4_K_M | 75.1 | Fits |
Mac Studio M3 Ultra 256GB | 256 GB | Q4_K_M | 65.2 | Fits |
Mac Studio M2 Ultra 128GB | 128 GB | Q4_K_M | 54.3 | Fits |
Mac Studio M1 Ultra 128GB | 128 GB | Q4_K_M | 51.5 | Fits |
MacBook Pro M4 Max 128GB | 128 GB | Q4_K_M | 35.4 | Fits |
MacBook Pro M4 Max 64GB | 64 GB | Q4_K_M | 35.4 | Fits |
| RTX 4070 12GB | 12 GB | Q4_K_M | 33.2 | Offloads |
MacBook Pro M3 Max 64GB | 64 GB | Q4_K_M | 28.1 | Fits |
MacBook Pro M1 Max 64GB | 64 GB | Q4_K_M | 25.8 | Fits |
MacBook Pro M4 Pro 48GB | 48 GB | Q4_K_M | 21.7 | Fits |
| RTX 3060 12GB | 12 GB | Q4_K_M | 19.5 | Offloads |
| RTX 4060 8GB | 8 GB | Q4_K_M | 7.2 | Too big |
Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.
How NousResearch Hermes 4 14B (14B params) fits at each quantization level on Quadro RTX 8000 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C42 |
Q3_K_S | 3 | 6.9 GB | Low | C42 |
NVFP4 | 4 | 7.8 GB | Medium | C42 |
Q4_K_M | 4 | 8.5 GB | Medium | C42 |
Q5_K_M | 5 | 10.1 GB | High | C43 |
Q6_K | 6 | 11.5 GB | High | C43 |
Q8_0 | 8 | 15.0 GB | Very High | C44 |
F16Best for your GPU | 16 | 28.7 GB | Maximum | C48 |
Copy-paste commands to run NousResearch Hermes 4 14B on your machine.
Run
lms load hf-bartowski--nousresearch-hermes-4-14b-gguf && lms server startUpgrade options
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 140%.
Adds memory headroom for longer context windows and future model growth.
~$10,000 MSRP
Yes, Quadro RTX 8000 48GB can run NousResearch Hermes 4 14B with a C grade (Runs well). Expected decode speed: 54.3 tok/s.
NousResearch Hermes 4 14B (14B parameters) requires approximately 16.2 GB of memory with Q4_K_M quantization.
The recommended quantization for NousResearch Hermes 4 14B is Q4_K_M, which balances quality and memory efficiency.
On Quadro RTX 8000 48GB, NousResearch Hermes 4 14B achieves approximately 54.3 tokens per second decode speed with a time-to-first-token of 3566ms using Q4_K_M quantization.
For coding workloads, NousResearch Hermes 4 14B on Quadro RTX 8000 48GB receives a C grade with 54.3 tok/s and 326K context.
On Quadro RTX 8000 48GB, NousResearch Hermes 4 14B can safely use up to 326K tokens of context. The model's official context limit is —, 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/hf-bartowski--nousresearch-hermes-4-14b-gguf-on-quadro-rtx-8000-48gb" 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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