Nous Hermes 2 SOLAR 10.7B needs ~15.6 GB VRAM. MacBook Pro M4 Pro 64GB has 46.1 GB. With Q4_K_M quantization, expect ~28 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
28.3 tok/s
TTFT
6831 ms
Safe context
405K
Memory
15.6 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 | 28.3 tok/s | 3726 ms | 405K |
| Coding | C | Runs well | 28.3 tok/s | 6831 ms | 405K |
| Agentic Coding | C | Runs well | 28.3 tok/s | 9936 ms | 405K |
| Reasoning | C | Runs well | 28.3 tok/s | 8073 ms | 405K |
| RAG | C | Runs well | 28.3 tok/s | 12420 ms | 405K |
How Nous Hermes 2 SOLAR 10.7B (10.699999809265137B params) fits at each quantization level on MacBook Pro M4 Pro 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.2 GB | Low | C42 |
Q3_K_S | 3 | 5.2 GB | Low | C42 |
NVFP4 | 4 |
Copy-paste commands to run Nous Hermes 2 SOLAR 10.7B on your machine.
Run
lms load hf-thebloke--nous-hermes-2-solar-10-7b-gguf && lms server startUpgrade options
Raises estimated decode speed by about 64%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Raises estimated decode speed by about 201%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Raises estimated decode speed by about 151%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, MacBook Pro M4 Pro 64GB can run Nous Hermes 2 SOLAR 10.7B with a C grade (Runs well). Expected decode speed: 28.3 tok/s.
Nous Hermes 2 SOLAR 10.7B (10.699999809265137B parameters) requires approximately 15.6 GB of memory with Q4_K_M quantization.
The recommended quantization for Nous Hermes 2 SOLAR 10.7B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Pro 64GB, Nous Hermes 2 SOLAR 10.7B achieves approximately 28.3 tokens per second decode speed with a time-to-first-token of 6831ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 2 SOLAR 10.7B on MacBook Pro M4 Pro 64GB receives a C grade with 28.3 tok/s and 405K context.
On MacBook Pro M4 Pro 64GB, Nous Hermes 2 SOLAR 10.7B can safely use up to 405K 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-thebloke--nous-hermes-2-solar-10-7b-gguf-on-m4-pro-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
6.0 GB |
| Medium |
| C42 |
Q4_K_M | 4 | 6.5 GB | Medium | C42 |
Q5_K_M | 5 | 7.7 GB | High | C42 |
Q6_K | 6 | 8.8 GB | High | C43 |
Q8_0 | 8 | 11.4 GB | Very High | C43 |
F16Best for your GPU | 16 | 21.9 GB | Maximum | C47 |
Not always. MacBook Pro M4 Pro 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.