Raises estimated decode speed by about 38%.
~$1,999 MSRP
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VOOZH | about |
Solar 7B needs ~11.6 GB VRAM. MacBook Pro M4 32GB has 23.0 GB. With Q4_K_M quantization, expect ~20 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
20.0 tok/s
TTFT
9674 ms
Safe context
8K
Memory
11.6 GB / 23.0 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 | B | Runs well | 20.2 tok/s | 5219 ms | 8K |
| Coding | B | Runs well | 20.2 tok/s | 9568 ms | 8K |
| Agentic Coding | A | Runs well | 20.2 tok/s | 13917 ms | 8K |
| Reasoning | B | Runs well | 20.2 tok/s | 11308 ms | 8K |
| RAG | A | Runs well | 20.2 tok/s | 17396 ms | 8K |
How Solar 7B (7B params) fits at each quantization level on MacBook Pro M4 32GB (23.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B65 |
Q3_K_S | 3 | 3.4 GB | Low | B65 |
NVFP4 | 4 |
Copy-paste commands to run Solar 7B on your machine.
Run
lms load Solar-7B && lms server startUpgrade options
Raises estimated decode speed by about 38%.
~$1,999 MSRP
Raises estimated decode speed by about 255%.
~$2,499 MSRP
Raises estimated decode speed by about 372%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
3.9 GB |
| Medium |
| B66 |
Q4_K_M | 4 | 4.3 GB | Medium | B66 |
Q5_K_M | 5 | 5.0 GB | High | B66 |
Q6_K | 6 | 5.7 GB | High | B67 |
Q8_0 | 8 | 7.5 GB | Very High | B68 |
F16Best for your GPU | 16 | 14.3 GB | Maximum | A71 |