SOLAR 10.7B Instruct v1.0 uncensored needs ~15.6 GB VRAM. MacBook Pro M1 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~34 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
33.7 tok/s
TTFT
5744 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 | 33.7 tok/s | 3133 ms | 405K |
| Coding | C | Runs well | 33.7 tok/s | 5744 ms | 405K |
| Agentic Coding | C | Runs well | 33.7 tok/s | 8355 ms | 405K |
| Reasoning | C | Runs well | 33.7 tok/s | 6788 ms | 405K |
| RAG | C | Runs well | 33.7 tok/s | 10443 ms | 405K |
How SOLAR 10.7B Instruct v1.0 uncensored (10.699999809265137B params) fits at each quantization level on MacBook Pro M1 Max 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 | 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 |
Copy-paste commands to run SOLAR 10.7B Instruct v1.0 uncensored on your machine.
Run
lms load hf-thebloke--solar-10-7b-instruct-v1-0-uncensored-gguf && lms server startUpgrade-Optionen
Raises estimated decode speed by about 153%.
Adds memory headroom for longer context windows and future model growth.
ca. $3,999 MSRP
Raises estimated decode speed by about 111%.
Adds memory headroom for longer context windows and future model growth.
ca. $3,999 MSRP
Raises estimated decode speed by about 100%.
Adds memory headroom for longer context windows and future model growth.
ca. $3,999 MSRP
Yes, MacBook Pro M1 Max 64GB can run SOLAR 10.7B Instruct v1.0 uncensored with a C grade (Runs well). Expected decode speed: 33.7 tok/s.
SOLAR 10.7B Instruct v1.0 uncensored (10.699999809265137B parameters) requires approximately 15.6 GB of memory with Q4_K_M quantization.
The recommended quantization for SOLAR 10.7B Instruct v1.0 uncensored is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M1 Max 64GB, SOLAR 10.7B Instruct v1.0 uncensored achieves approximately 33.7 tokens per second decode speed with a time-to-first-token of 5744ms using Q4_K_M quantization.
For coding workloads, SOLAR 10.7B Instruct v1.0 uncensored on MacBook Pro M1 Max 64GB receives a C grade with 33.7 tok/s and 405K context.
On MacBook Pro M1 Max 64GB, SOLAR 10.7B Instruct v1.0 uncensored can safely use up to 405K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. MacBook Pro M1 Max 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.
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<iframe src="https://willitrunai.com/embed/hf-thebloke--solar-10-7b-instruct-v1-0-uncensored-gguf-on-m1-max-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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