RTX PRO 5000 Blackwell 48GBBudget pick1344 GB/s (+798)
C
Raises estimated decode speed by about 88%.51.4 tok/s decode
Raises estimated decode speed by about 88%.
~$4,999 MSRP
Hermes 4.3 36B needs ~34.0 GB VRAM. MacBook Pro M4 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~27 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
27.3 tok/s
TTFT
7079 ms
Safe context
62K
Memory
34.0 GB / 46.1 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 | 27.3 tok/s | 3861 ms | 62K |
| Coding | C | Runs well | 27.3 tok/s | 7079 ms | 62K |
| Agentic Coding | C | Tight fit | 27.3 tok/s | 10296 ms | 62K |
| Reasoning | C | Runs well | 27.3 tok/s | 8366 ms | 62K |
| RAG | C | Tight fit | 27.3 tok/s | 12871 ms | 62K |
How Hermes 4.3 36B (36B params) fits at each quantization level on MacBook Pro M4 Max 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 14.0 GB | Low | C45 |
Q3_K_S | 3 | 17.6 GB | Low | C46 |
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
RTX PRO 5000 Blackwell 48GBBudget pickRaises estimated decode speed by about 88%.
~$4,999 MSRP
RTX 6000 Ada 48GBBest valueRaises estimated decode speed by about 31%.
~$6,800 MSRP
Yes, MacBook Pro M4 Max 64GB can run Hermes 4.3 36B with a C grade (Runs well). Expected decode speed: 27.3 tok/s.
Hermes 4.3 36B (36B parameters) requires approximately 34.0 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 MacBook Pro M4 Max 64GB, Hermes 4.3 36B achieves approximately 27.3 tokens per second decode speed with a time-to-first-token of 7079ms using Q4_K_M quantization.
For coding workloads, Hermes 4.3 36B on MacBook Pro M4 Max 64GB receives a C grade with 27.3 tok/s and 62K context.
On MacBook Pro M4 Max 64GB, Hermes 4.3 36B can safely use up to 62K 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-m4-max-64gb" 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 |
| C47 |
Q4_K_M | 4 | 22.0 GB | Medium | C47 |
Q5_K_M | 5 | 25.9 GB | High | C48 |
Q6_KBest for your GPU | 6 | 29.5 GB | High | C48 |
Q8_0 | 8 | 38.5 GB | Very High | F0 |
F16 | 16 | 73.8 GB | Maximum | F0 |
Not always. MacBook Pro M4 Max 64GB 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.