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URL: https://willitrunai.com/can-run/gemma-2-27b-on-m2-ultra-64gb

⇱ Gemma 2 27B on Mac Studio M2 Ultra 64GB? YES

Can Gemma 2 27B run on Mac Studio M2 Ultra 64GB?

YES — Runs Great

A72Great
○Estimated from fit model

Gemma 2 27B needs ~35.5 GB VRAM. Mac Studio M2 Ultra 64GB has 46.1 GB. With Q4_K_M quantization, expect ~22 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) — 35.5 GB, 22.4 tok/s, Runs well
35.5 GB required46.1 GB available
77% VRAM used

Fit status

Runs well

Decode

22.4 tok/s

TTFT

8636 ms

Safe context

8K

Memory

35.5 GB / 46.1 GB

Memory breakdown

Weights16.5 GB
KV Cache11.2 GB
Runtime0.9 GB
Headroom6.9 GB

See how fast it feels

See how fast it feelsGemma 2 27B 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: 22.4 tok/s decode · 8.6s TTFT (warm) · 56 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 well22.4 tok/s4710 ms8K
CodingARuns well22.4 tok/s8636 ms8K
Agentic CodingBRuns with offload (needs ~0.2 GB host RAM)21.7 tok/s12993 ms8K
ReasoningARuns well22.4 tok/s10206 ms8K
RAGBRuns with offload (needs ~0.2 GB host RAM)21.7 tok/s16241 ms8K

Quantization options

How Gemma 2 27B (27B params) fits at each quantization level on Mac Studio M2 Ultra 64GB (46.1 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
10.5 GB
LowB63
Q3_K_S
3
13.2 GB
LowB64
NVFP4
4
15.1 GB
MediumB64
Q4_K_M
4
16.5 GB
MediumB65
Q5_K_M
5
19.4 GB
HighB66
Q6_K
6
22.1 GB
HighB67
Q8_0Best for your GPU
8
28.9 GB
Very HighB68
F16
16
55.4 GB
MaximumF0

Get started

Copy-paste commands to run Gemma 2 27B on your machine.

Run

ollama run gemma2:27b

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 3.6 35B A3B		35BS59 tok/s
👁 Alibaba
Qwen3-VL 30B A3B Instruct		30BS72.6 tok/s
👁 Alibaba
Qwen 3.5 35B A3B		35BS64.1 tok/s
👁 Alibaba
Qwen 3 32B		32BS25.9 tok/s

Frequently asked questions

See all results for Mac Studio M2 Ultra 64GBSee all hardware for Gemma 2 27B