Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored needs ~42.7 GB VRAM. MacBook Pro M3 Max 64GB has 46.1 GB. With Q4_K_M quantization, expect ~8 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
8.2 tok/s
TTFT
23619 ms
Safe context
26K
Memory
42.7 GB / 46.1 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 | 8.2 tok/s | 12883 ms | 26K |
| Coding | C | Tight fit | 8.2 tok/s | 23619 ms | 26K |
| Agentic Coding | C | Runs with offload (needs ~1.4 GB host RAM) | 7.5 tok/s | 37601 ms | 26K |
| Reasoning | C | Tight fit | 8.2 tok/s | 27914 ms | 26K |
| RAG | C | Runs with offload (needs ~1.4 GB host RAM) | 7.5 tok/s | 47001 ms | 26K |
How Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored (48B params) fits at each quantization level on MacBook Pro M3 Max 64GB (46.1 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.7 GB | Low | C46 |
Q3_K_S | 3 | 23.5 GB | Low | C48 |
NVFP4 | 4 | 26.9 GB | Medium | C48 |
Q4_K_M | 4 | 29.3 GB | Medium | C48 |
Q5_K_MBest for your GPU | 5 | 34.6 GB | High | C48 |
Q6_K | 6 | 39.4 GB | High | F0 |
Q8_0 | 8 | 51.4 GB | Very High | F0 |
F16 | 16 | 98.4 GB | Maximum | F0 |
Copy-paste commands to run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored on your machine.
Run
lms load hf-davidau--qwen3-48b-a4b-savant-commander-distill-12x-closed-open-heretic-uncensored-gguf && lms server startOpções de upgrade
Raises estimated decode speed by about 150%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
Adds memory headroom for longer context windows and future model growth.
~$3,199 MSRP
Raises estimated decode speed by about 132%.
Adds memory headroom for longer context windows and future model growth.
~$3,999 MSRP
Yes, MacBook Pro M3 Max 64GB can run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored with a C grade (Tight fit). Expected decode speed: 8.2 tok/s.
Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored (48B parameters) requires approximately 42.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored is Q4_K_M, which balances quality and memory efficiency.
On MacBook Pro M3 Max 64GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored achieves approximately 8.2 tokens per second decode speed with a time-to-first-token of 23619ms using Q4_K_M quantization.
For coding workloads, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored on MacBook Pro M3 Max 64GB receives a C grade with 8.2 tok/s and 26K context.
On MacBook Pro M3 Max 64GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored can safely use up to 26K 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 M3 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.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/hf-davidau--qwen3-48b-a4b-savant-commander-distill-12x-closed-open-heretic-uncensored-gguf-on-m3-max-64gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: