Will It Run AI

Can Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored run on MacBook Pro M4 Pro 48GB?

BARELY — Tight on Memory

D31Poor
Estimated — low-sample bucket· few comparable runs

Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored needs ~41.0 GB VRAM. MacBook Pro M4 Pro 48GB has 34.6 GB. With Q4_K_M quantization, expect ~10 tok/s.

Runtime: llama.cppCapacity: OffloadBandwidth: LowStack: StandardBottleneck: Host offload
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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.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) 41.0 GB, 10.0 tok/s, Very compromised (needs ~4.6 GB host RAM)
41.0 GB required34.6 GB available
118% VRAM needed

6.4 GB over capacity — needs offload or smaller quantization

Fit status

Very compromised (needs ~4.6 GB host RAM)

Decode

10.0 tok/s

TTFT

19385 ms

Safe context

4K

Memory

41.0 GB / 34.6 GB

Offload

20%

Memory breakdown

Weights29.3 GB
KV Cache5.6 GB
Runtime0.9 GB
Headroom5.2 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 Pro 48GB
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: 10.0 tok/s decode · 19.4s TTFT (warm) · 25 tok/s prefill

What limits this setup

It fits through host-memory offload, and offload is the main reason performance drops.

CPU or host-memory offload is active

About 20% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.

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.

Best improvement path

Remove offload with more accelerator memory

Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Increase host RAM if you keep offloading

This setup may need roughly 4.6 GB of extra host RAM just for the offloaded portion, before OS and other tools.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatDVery compromised (needs ~2.8 GB host RAM)11.0 tok/s9634 ms4K
CodingDVery compromised (needs ~4.6 GB host RAM)10.0 tok/s19385 ms4K
Agentic CodingFToo heavy8.5 tok/s32963 ms4K
ReasoningDVery compromised (needs ~4.6 GB host RAM)10.0 tok/s22910 ms4K
RAGFToo heavy8.5 tok/s41203 ms4K

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 Pro 48GB (34.6 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
18.7 GB
LowC49
Q3_K_S
3
23.5 GB
LowC48
NVFP4Best for your GPU
4
26.9 GB
MediumC48
Q4_K_M
4
29.3 GB
MediumF0
Q5_K_M
5
34.6 GB
HighF0
Q6_K
6
39.4 GB
HighF0
Q8_0
8
51.4 GB
Very HighF0
F16
16
98.4 GB
MaximumF0

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 start

Opciones de mejora

Hardware que ejecuta bien Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored

Frequently asked questions

Can MacBook Pro M4 Pro 48GB run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored?

Yes, MacBook Pro M4 Pro 48GB can run Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored with a D grade (Very compromised (needs ~4.6 GB host RAM)). Expected decode speed: 10.0 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 41.0 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 Pro 48GB?

On MacBook Pro M4 Pro 48GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored achieves approximately 10.0 tokens per second decode speed with a time-to-first-token of 19385ms using Q4_K_M quantization.

Can MacBook Pro M4 Pro 48GB 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 Pro 48GB receives a D grade with 10.0 tok/s and 4K context.

What context window can Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored use on MacBook Pro M4 Pro 48GB?

On MacBook Pro M4 Pro 48GB, Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored can safely use up to 4K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

What should I upgrade first if Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored feels slow on MacBook Pro M4 Pro 48GB?

Remove offload with more accelerator memory. Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.

Is unified memory on MacBook Pro M4 Pro 48GB as fast as VRAM for Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored?

Not always. MacBook Pro M4 Pro 48GB 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.

See all results for MacBook Pro M4 Pro 48GBSee all hardware for Qwen3 48B A4B Savant Commander Distill 12X Closed Open Heretic Uncensored
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