Nous Hermes 1.0 needs ~25.5 GB VRAM. Mac Studio M2 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~85 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
84.5 tok/s
TTFT
2291 ms
Safe context
16K
Memory
25.5 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 | A | Runs well | 84.5 tok/s | 1249 ms | 16K |
| Coding | A | Runs well | 84.5 tok/s | 2291 ms | 16K |
| Agentic Coding | A | Runs well | 84.5 tok/s | 3332 ms | 16K |
| Reasoning | A | Runs well | 84.5 tok/s | 2707 ms | 16K |
| RAG | A | Runs well | 84.5 tok/s | 4165 ms | 16K |
How Nous Hermes 1.0 (9B params) fits at each quantization level on Mac Studio M2 Ultra 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.5 GB | Low | B62 |
Q3_K_S | 3 | 4.4 GB | Low | B62 |
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 | 70.2 tok/s | |
| Qwen 3.5 27B | 27B | S | 30.4 tok/s |
Yes, Mac Studio M2 Ultra 64GB can run Nous Hermes 1.0 with a A grade (Runs well). Expected decode speed: 84.5 tok/s.
Nous Hermes 1.0 (9B parameters) requires approximately 25.5 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 Mac Studio M2 Ultra 64GB, Nous Hermes 1.0 achieves approximately 84.5 tokens per second decode speed with a time-to-first-token of 2291ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 1.0 on Mac Studio M2 Ultra 64GB receives a A grade with 84.5 tok/s and 16K context.
On Mac Studio M2 Ultra 64GB, 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-m2-ultra-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
5.0 GB |
| Medium |
| B62 |
Q4_K_M | 4 | 5.5 GB | Medium | B63 |
Q5_K_M | 5 | 6.5 GB | High | B63 |
Q6_K | 6 | 7.4 GB | High | B63 |
Q8_0 | 8 | 9.6 GB | Very High | B64 |
F16Best for your GPU | 16 | 18.5 GB | Maximum | B66 |
| Qwen 3.6 27B | 27B | S | 23.1 tok/s |
| Qwen 3.6 35B A3B | 35B | S | 59 tok/s |
| Qwen3-VL 30B A3B Instruct | 30B | S | 72.6 tok/s |
Not always. Mac Studio M2 Ultra 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.