Solar Open 100B i1 needs ~87.4 GB VRAM. MacBook Pro M4 Max 128GB has 92.2 GB. With Q4_K_M quantization, expect ~10 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
9.8 tok/s
TTFT
19663 ms
Safe context
22K
Memory
87.4 GB / 92.2 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
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.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Tight fit | 9.8 tok/s | 10725 ms | 22K |
| Coding | C | Tight fit | 9.8 tok/s | 19663 ms | 22K |
| Agentic Coding | D | Runs with offload (needs ~4.3 GB host RAM) | 8.7 tok/s | 32500 ms | 22K |
| Reasoning | C | Tight fit | 9.8 tok/s | 23239 ms | 22K |
| RAG | D | Runs with offload (needs ~4.3 GB host RAM) | 8.7 tok/s | 40625 ms | 22K |
How Solar Open 100B i1 (100B params) fits at each quantization level on MacBook Pro M4 Max 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 39.0 GB | Low | C45 |
Q3_K_S | 3 | 49.0 GB | Low | C48 |
NVFP4 | 4 | 56.0 GB | Medium | C48 |
Q4_K_M | 4 | 61.0 GB | Medium | C48 |
Q5_K_MBest for your GPU | 5 | 72.0 GB | High | C48 |
Q6_K | 6 | 82.0 GB | High | F0 |
Q8_0 | 8 | 107.0 GB | Very High | F0 |
F16 | 16 | 205.0 GB | Maximum | F0 |
Copy-paste commands to run Solar Open 100B i1 on your machine.
Run
lms load hf-mradermacher--solar-open-100b-i1-gguf && lms server startアップグレードオプション
Raises estimated decode speed by about 877%.
Adds memory headroom for longer context windows and future model growth.
〜$8,000 MSRP
RTX PRO 6000 Blackwell Workstation Edition 96GBコスパ最良Raises estimated decode speed by about 152%.
〜$9,999 MSRP
Raises estimated decode speed by about 520%.
Adds memory headroom for longer context windows and future model growth.
〜$12,000 MSRP
Yes, MacBook Pro M4 Max 128GB can run Solar Open 100B i1 with a C grade (Tight fit). Expected decode speed: 9.8 tok/s.
Solar Open 100B i1 (100B parameters) requires approximately 87.4 GB of memory with Q4_K_M quantization.
The recommended quantization for Solar Open 100B i1 is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M4 Max 128GB, Solar Open 100B i1 achieves approximately 9.8 tokens per second decode speed with a time-to-first-token of 19663ms using Q4_K_M quantization.
For coding workloads, Solar Open 100B i1 on MacBook Pro M4 Max 128GB receives a C grade with 9.8 tok/s and 22K context.
On MacBook Pro M4 Max 128GB, Solar Open 100B i1 can safely use up to 22K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Not always. MacBook Pro M4 Max 128GB 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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