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URL: https://willitrunai.com/can-run/wizardlm-13b-on-m2-ultra-64gb

⇱ WizardLM 13B on Mac Studio M2 Ultra 64GB? YES

Can WizardLM 13B run on Mac Studio M2 Ultra 64GB?

YES — Runs Great

A74Great
○Estimated from fit model

WizardLM 13B needs ~27.9 GB VRAM. Mac Studio M2 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~59 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: 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) — 27.9 GB, 58.5 tok/s, Runs well
27.9 GB required46.1 GB available
61% VRAM used

Fit status

Runs well

Decode

58.5 tok/s

TTFT

3309 ms

Safe context

8K

Memory

27.9 GB / 46.1 GB

Memory breakdown

Weights7.9 GB
KV Cache12.2 GB
Runtime0.9 GB
Headroom6.9 GB

See how fast it feels

See how fast it feelsWizardLM 13B on Mac Studio M2 Ultra 64GB
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: 58.5 tok/s decode · 3.3s TTFT (warm) · 146 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 well58.5 tok/s1805 ms8K
CodingARuns well58.5 tok/s3309 ms8K
Agentic CodingATight fit58.5 tok/s4813 ms8K
ReasoningARuns well58.5 tok/s3910 ms8K
RAGATight fit58.5 tok/s6016 ms8K

Quantization options

How WizardLM 13B (13B params) fits at each quantization level on Mac Studio M2 Ultra 64GB (46.1 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.1 GB
LowB63
Q3_K_S
3
6.4 GB
LowB63
NVFP4
4
7.3 GB
MediumB63
Q4_K_M
4
7.9 GB
MediumB63
Q5_K_M
5
9.4 GB
HighB64
Q6_K
6
10.7 GB
HighB64
Q8_0
8
13.9 GB
Very HighB65
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 Mac Studio M2 Ultra 64GB can run

ModelParamsGradeDecodeCapabilities
👁 Alibaba
Qwen3-Coder 30B A3B Instruct		30.5BS70.2 tok/s
👁 Alibaba
Qwen 3.5 27B		27BS30.4 tok/s
👁 Alibaba
Qwen 3.6 27B		27BS23.1 tok/s
👁 Alibaba
Qwen 3.6 35B A3B		35BS59 tok/s
👁 Alibaba
Qwen3-VL 30B A3B Instruct		30BS72.6 tok/s

Frequently asked questions

See all results for Mac Studio M2 Ultra 64GBSee all hardware for WizardLM 13B