GoogleGemma 3 27B on Apple M2 (8GB Unified)
M2 (8GB Unified) cannot run Gemma 3 27B. 8 GB VRAM is insufficient at any quantization level.
Model Size
27.23B
Device VRAM
8 GB
Bandwidth
100 GB/s
Quantization
Q4_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Gemma 3 27B on Apple M2 (8GB Unified) at Q4_K_M. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q4_K_M | – | – | ✗ Offload | Not viable | estimated |
Notes
Q4_K_M
Smallest quantization requires more than the ~5.5GB available on this 8GB Mac.
About Gemma 3 27B
Gemma 3 27B (27.23B) is a chat, coding, reasoning, multi-purpose model. Google's largest open-weight model before Gemma 4. Capable reasoning and instruction following. At 27B parameters, it sits between 8B models (too limited) and 70B models (too expensive). Wide multilingual support. Fits on 24 GB GPUs at Q4.
View all Gemma 3 27B hardware options →About Apple M2 (8GB Unified)
Apple M2 (8GB Unified) has 8 GB at 100 GB/s. Available in MacBook Air 13" (2022), MacBook Air 15" (2023), MacBook Pro 13" (2022).
See all models Apple M2 (8GB Unified) can run →Estimate method: Estimated: model exceeds 8GB Mac usable VRAM. Reference hardware source: github.com (2026-04-18)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.