Nous Hermes 1.0 needs ~23.8 GB VRAM. MacBook Pro M3 Max 48GB has 34.6 GB. With Q4_K_M quantization, expect ~44 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
43.7 tok/s
TTFT
4429 ms
Safe context
16K
Memory
23.8 GB / 34.6 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 | A | Runs well | 43.7 tok/s | 2416 ms | 16K |
| Coding | A | Runs well | 43.7 tok/s | 4429 ms | 16K |
| Agentic Coding | A | Runs with offload (needs ~0.2 GB host RAM) | 40.4 tok/s | 6969 ms | 16K |
| Reasoning | A | Runs well | 43.7 tok/s | 5234 ms | 16K |
| RAG | A | Runs with offload (needs ~0.2 GB host RAM) | 40.4 tok/s | 8711 ms |
How Nous Hermes 1.0 (9B params) fits at each quantization level on MacBook Pro M3 Max 48GB (34.6 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B63 |
Q3_K_S | 3 | 4.4 GB | Low | B64 |
NVFP4 | 4 |
Copy-paste commands to run Nous Hermes 1.0 on your machine.
Run
lms load Nous-Hermes-1.0 && lms server startYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen3-Coder 30B A3B Instruct | 30.5B | S | 36.3 tok/s | |
| Qwen 3.5 27B | 27B | S | 15.7 tok/s |
Yes, MacBook Pro M3 Max 48GB can run Nous Hermes 1.0 with a A grade (Runs well). Expected decode speed: 43.7 tok/s.
Nous Hermes 1.0 (9B parameters) requires approximately 23.8 GB of memory with Q4_K_M quantization.
The recommended quantization for Nous Hermes 1.0 is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M3 Max 48GB, Nous Hermes 1.0 achieves approximately 43.7 tokens per second decode speed with a time-to-first-token of 4429ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on MacBook Pro M3 Max 48GB receives a A grade with 43.7 tok/s and 16K context.
On MacBook Pro M3 Max 48GB, Nous Hermes 1.0 can safely use up to 16K tokens of context. The model's official context limit is 16K, 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/nous-hermes-1.0-on-m3-max-48gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 16K |
5.0 GB |
| Medium |
| B64 |
Q4_K_M | 4 | 5.5 GB | Medium | B64 |
Q5_K_M | 5 | 6.5 GB | High | B64 |
Q6_K | 6 | 7.4 GB | High | B65 |
Q8_0 | 8 | 9.6 GB | Very High | B66 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | B70 |
| Qwen 3.6 27B | 27B | S | 12 tok/s |
| Qwen 3.6 35B A3B | 35B | S | 33.5 tok/s |
| Qwen3-VL 30B A3B Instruct | 30B | S | 37.5 tok/s |
Not always. MacBook Pro M3 Max 48GB 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.