Raises estimated decode speed by about 947%.
Adds memory headroom for longer context windows and future model growth.
~$8,000 MSRP
Hermes 4.3 36B needs ~54.7 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 GB. With Q4_K_M quantization, expect ~25 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
25.4 tok/s
TTFT
7634 ms
Safe context
507K
Memory
54.7 GB / 184.3 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 25.4 tok/s | 4164 ms | 507K |
| Coding | C | Runs well | 25.4 tok/s | 7634 ms | 507K |
| Agentic Coding | C | Runs well | 25.4 tok/s | 11104 ms | 507K |
| Reasoning | C | Runs well | 25.4 tok/s | 9022 ms | 507K |
| RAG | C | Runs well | 25.4 tok/s | 13880 ms | 507K |
How Hermes 4.3 36B (36B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 14.0 GB | Low | D37 |
Q3_K_S | 3 | 17.6 GB | Low | D37 |
NVFP4 | 4 |
Copy-paste commands to run Hermes 4.3 36B on your machine.
Run
lms load hf-nousresearch--hermes-4-3-36b-gguf && lms server startUpgrade options
Raises estimated decode speed by about 947%.
Adds memory headroom for longer context windows and future model growth.
~$8,000 MSRP
Raises estimated decode speed by about 641%.
~$15,000 MSRP
Yes, Mac Studio M3 Ultra 256GB can run Hermes 4.3 36B with a C grade (Runs well). Expected decode speed: 25.4 tok/s.
Hermes 4.3 36B (36B parameters) requires approximately 54.7 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 Mac Studio M3 Ultra 256GB, Hermes 4.3 36B achieves approximately 25.4 tokens per second decode speed with a time-to-first-token of 7634ms using Q4_K_M quantization.
For coding workloads, Hermes 4.3 36B on Mac Studio M3 Ultra 256GB receives a C grade with 25.4 tok/s and 507K context.
On Mac Studio M3 Ultra 256GB, Hermes 4.3 36B can safely use up to 507K 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-nousresearch--hermes-4-3-36b-gguf-on-m3-ultra-256gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
20.2 GB |
| Medium |
| D37 |
Q4_K_M | 4 | 22.0 GB | Medium | D38 |
Q5_K_M | 5 | 25.9 GB | High | D38 |
Q6_K | 6 | 29.5 GB | High | D39 |
Q8_0 | 8 | 38.5 GB | Very High | D40 |
F16Best for your GPU | 16 | 73.8 GB | Maximum | C44 |
Not always. Mac Studio M3 Ultra 256GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.