solar finalised finetuned Model 10.7B i1 needs ~36.3 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 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
85.3 tok/s
TTFT
2269 ms
Safe context
1.9M
Memory
36.3 GB / 184.3 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 | 85.3 tok/s | 1238 ms | 1.9M |
| Coding | C | Runs well | 85.3 tok/s | 2269 ms | 1.9M |
| Agentic Coding | C | Runs well | 85.3 tok/s | 3300 ms | 1.9M |
| Reasoning | C | Runs well | 85.3 tok/s | 2681 ms | 1.9M |
| RAG | C | Runs well | 85.3 tok/s | 4125 ms | 1.9M |
How solar finalised finetuned Model 10.7B i1 (10.699999809265137B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 4.2 GB | Low | D37 |
Q3_K_S | 3 | 5.2 GB | Low | D37 |
NVFP4 | 4 |
Copy-paste commands to run solar finalised finetuned Model 10.7B i1 on your machine.
Run
lms load hf-mradermacher--solar-finalised-finetuned-model-10-7b-i1-gguf && lms server startYes, Mac Studio M3 Ultra 256GB can run solar finalised finetuned Model 10.7B i1 with a C grade (Runs well). Expected decode speed: 85.3 tok/s.
solar finalised finetuned Model 10.7B i1 (10.699999809265137B parameters) requires approximately 36.3 GB of memory with Q4_K_M quantization.
The recommended quantization for solar finalised finetuned Model 10.7B i1 is Q4_K_M, which balances quality and memory efficiency.
On Mac Studio M3 Ultra 256GB, solar finalised finetuned Model 10.7B i1 achieves approximately 85.3 tokens per second decode speed with a time-to-first-token of 2269ms using Q4_K_M quantization.
For coding workloads, solar finalised finetuned Model 10.7B i1 on Mac Studio M3 Ultra 256GB receives a C grade with 85.3 tok/s and 1.9M context.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-mradermacher--solar-finalised-finetuned-model-10-7b-i1-gguf-on-m3-ultra-256gb" 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 |
| D37 |
Q4_K_M | 4 | 6.5 GB | Medium | D37 |
Q5_K_M | 5 | 7.7 GB | High | D37 |
Q6_K | 6 | 8.8 GB | High | D37 |
Q8_0 | 8 | 11.4 GB | Very High | D37 |
F16Best for your GPU | 16 | 21.9 GB | Maximum | D37 |
On Mac Studio M3 Ultra 256GB, solar finalised finetuned Model 10.7B i1 can safely use up to 1.9M tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Not always. Mac Studio M3 Ultra 256GB 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.