RTX PRO 6000 Blackwell Workstation Edition 96GBGünstige Wahl1792 GB/s (+1246)
C
Raises estimated decode speed by about 151%.51.4 tok/s Dekodierung
Raises estimated decode speed by about 151%.
ca. $9,999 MSRP
Can Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored run on MacBook Pro M4 Max 128GB?
YES — Runs Great
C48Usable
Estimated from fit model
Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored needs ~49.6 GB VRAM. MacBook Pro M4 Max 128GB has 92.2 GB. With Q4_K_M quantization, expect ~21 tok/s.
Runtime: llama.cppCapacity: RoomyBandwidth: MediumStack: StandardBottleneck: Balanced
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 49.6 GB, 20.5 tok/s, Runs well
49.6 GB required92.2 GB available
54% VRAM used
Fit status
Runs well
Decode
20.5 tok/s
TTFT
9438 ms
Safe context
137K
Memory
49.6 GB / 92.2 GB
Memory breakdown
Weights29.3 GB
KV Cache5.6 GB
Runtime0.9 GB
Headroom13.8 GB
See how fast it feels
See how fast it feelsQwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored on MacBook Pro M4 Max 128GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 20.5 tok/s decode · 9.4s TTFT (warm) · 51 tok/s prefill
What limits this setup
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.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs well | 20.5 tok/s | 5148 ms | 137K |
| Coding | C | Runs well | 20.5 tok/s | 9438 ms | 137K |
| Agentic Coding | C | Runs well | 20.5 tok/s | 13729 ms | 137K |
| Reasoning | C | Runs well | 20.5 tok/s | 11154 ms | 137K |
| RAG | C | Runs well | 20.5 tok/s | 17161 ms | 137K |
Quantization options
How Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored (48B params) fits at each quantization level on MacBook Pro M4 Max 128GB (92.2 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 18.7 GB | Low | C41 |
Q3_K_S | 3 | 23.5 GB | Low | C41 |
NVFP4 | 4 | 26.9 GB | Medium | C42 |
Q4_K_M | 4 | 29.3 GB | Medium | C43 |
Q5_K_M | 5 | 34.6 GB | High | C44 |
Q6_K | 6 | 39.4 GB | High | C45 |
Q8_0Best for your GPU | 8 | 51.4 GB | Very High | C48 |
F16 | 16 | 98.4 GB | Maximum | F0 |
Get started
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 startUpgrade-Optionen
Hardware, die Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored gut ausführt
Frequently asked questions
Can MacBook Pro M4 Max 128GB run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored?
Yes, MacBook Pro M4 Max 128GB can run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored with a C grade (Runs well). Expected decode speed: 20.5 tok/s.
How much VRAM does Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored need?
Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored (48B parameters) requires approximately 49.6 GB of memory with Q4_K_M quantization.
What is the best quantization for Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored?
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.
What speed will Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored run at on MacBook Pro M4 Max 128GB?
On MacBook Pro M4 Max 128GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored achieves approximately 20.5 tokens per second decode speed with a time-to-first-token of 9438ms using Q4_K_M quantization.
Can MacBook Pro M4 Max 128GB run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored for coding?
For coding workloads, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored on MacBook Pro M4 Max 128GB receives a C grade with 20.5 tok/s and 137K context.
What context window can Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored use on MacBook Pro M4 Max 128GB?
On MacBook Pro M4 Max 128GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored can safely use up to 137K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
Is unified memory on MacBook Pro M4 Max 128GB as fast as VRAM for Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored?
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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