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URL: https://willitrunai.com/can-run/wizardlm-13b-on-m3-max-48gb

⇱ WizardLM 13B on MacBook Pro M3 Max 48GB? YES

Can WizardLM 13B run on MacBook Pro M3 Max 48GB?

YES — Runs Great

A74Great
○Estimated from fit model

WizardLM 13B needs ~26.2 GB VRAM. MacBook Pro M3 Max 48GB has 34.6 GB. With Q4_K_M quantization, expect ~30 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: LowStack: StandardBottleneck: Balanced
Share:

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) — 26.2 GB, 30.3 tok/s, Runs well
26.2 GB required34.6 GB available
76% VRAM used

Fit status

Runs well

Decode

30.3 tok/s

TTFT

6397 ms

Safe context

8K

Memory

26.2 GB / 34.6 GB

Memory breakdown

Weights7.9 GB
KV Cache12.2 GB
Runtime0.9 GB
Headroom5.2 GB

See how fast it feels

See how fast it feelsWizardLM 13B on MacBook Pro M3 Max 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: 30.3 tok/s decode · 6.4s TTFT (warm) · 76 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

WorkloadGradeFitDecodeTTFTContext
ChatARuns well30.3 tok/s3489 ms8K
CodingARuns well30.3 tok/s6397 ms8K
Agentic CodingBVery compromised (needs ~0.8 GB host RAM)25.4 tok/s11068 ms8K
ReasoningARuns well30.3 tok/s7560 ms8K
RAGBVery compromised (needs ~0.8 GB host RAM)25.4 tok/s13835 ms8K

Quantization options

How WizardLM 13B (13B params) fits at each quantization level on MacBook Pro M3 Max 48GB (34.6 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.1 GB
LowB64
Q3_K_S
3
6.4 GB
LowB64
NVFP4
4
7.3 GB
MediumB65
Q4_K_M
4
7.9 GB
MediumB65
Q5_K_M
5
9.4 GB
HighB65
Q6_K
6
10.7 GB
HighB66
Q8_0
8
13.9 GB
Very HighB67
F16Best for your GPU
16
26.7 GB
MaximumB69

Get started

Copy-paste commands to run WizardLM 13B on your machine.

Run

lms load WizardLM-13B-V1.0 && lms server start

Your hardware

More models your MacBook Pro M3 Max 48GB can run

ModelParamsGradeDecodeCapabilities
👁 Alibaba
Qwen3-Coder 30B A3B Instruct		30.5BS36.3 tok/s
👁 Alibaba
Qwen 3.5 27B		27BS15.7 tok/s
👁 Alibaba
Qwen 3.6 27B		27BS12 tok/s
👁 Alibaba
Qwen 3.6 35B A3B		35BS33.5 tok/s
👁 Alibaba
Qwen3-VL 30B A3B Instruct		30BS37.5 tok/s

Frequently asked questions

See all results for MacBook Pro M3 Max 48GBSee all hardware for WizardLM 13B