MacBook Air M4 24GBBudget pick
24 GB Unified (+8)
C
Adds memory headroom for longer context windows and future model growth.11.6 tok/s decode
Adds memory headroom for longer context windows and future model growth.
~$1,099 MSRP
Nous Hermes 2 SOLAR 10.7B needs ~10.4 GB VRAM. MacBook Pro M2 Pro 16GB has 11.5 GB. With Q4_K_M quantization, expect ~21 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
Tight fit
Decode
21.4 tok/s
TTFT
9026 ms
Safe context
30K
Memory
10.4 GB / 11.5 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 | Tight fit | 21.4 tok/s | 4923 ms | 30K |
| Coding | C | Tight fit | 21.4 tok/s | 9026 ms | 30K |
| Agentic Coding | C | Runs with offload (needs ~0.1 GB host RAM) | 20.8 tok/s | 13528 ms | 30K |
| Reasoning | C | Tight fit | 21.4 tok/s | 10667 ms | 30K |
| RAG | C | Runs with offload (needs ~0.1 GB host RAM) | 20.8 tok/s | 16910 ms |
How Nous Hermes 2 SOLAR 10.7B (10.699999809265137B params) fits at each quantization level on MacBook Pro M2 Pro 16GB (11.5 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.2 GB | Low | C51 |
Q3_K_S | 3 | 5.2 GB | Low | C53 |
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
Adds memory headroom for longer context windows and future model growth.
~$1,099 MSRP
Raises estimated decode speed by about 32%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
~$1,999 MSRP
Yes, MacBook Pro M2 Pro 16GB can run Nous Hermes 2 SOLAR 10.7B with a C grade (Tight fit). Expected decode speed: 21.4 tok/s.
Nous Hermes 2 SOLAR 10.7B (10.699999809265137B parameters) requires approximately 10.4 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 M2 Pro 16GB, Nous Hermes 2 SOLAR 10.7B achieves approximately 21.4 tokens per second decode speed with a time-to-first-token of 9026ms using Q4_K_M quantization.
For coding workloads, Nous Hermes 2 SOLAR 10.7B on MacBook Pro M2 Pro 16GB receives a C grade with 21.4 tok/s and 30K context.
On MacBook Pro M2 Pro 16GB, Nous Hermes 2 SOLAR 10.7B can safely use up to 30K 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-m2-pro-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
| 30K |
6.0 GB |
| Medium |
| C52 |
Q4_K_M | 4 | 6.5 GB | Medium | C52 |
Q5_K_MBest for your GPU | 5 | 7.7 GB | High | C52 |
Q6_K | 6 | 8.8 GB | High | F0 |
Q8_0 | 8 | 11.4 GB | Very High | F0 |
F16 | 16 | 21.9 GB | Maximum | F0 |
Not always. MacBook Pro M2 Pro 16GB 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.