MicrosoftPhi-4 Mini on Apple M3 (8GB Unified)
Yes — M3 (8GB Unified) handles Phi-4 Mini well at Q8_0 — 16 tok/s. Solid daily-driver performance on 8 GB VRAM.
Model Size
3.82B
Device VRAM
8 GB
Bandwidth
100 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-4 Mini on Apple M3 (8GB Unified) at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 16 tok/s | – | ✓ Yes | Good | estimated |
Notes
Q8_0
Conservative estimate. Uses Q8_0 (4.3GB), the highest-quality format that fits within ~5.5GB usable memory.
About Phi-4 Mini
Phi-4 Mini (3.82B) is a chat, coding, ai coding, reasoning model. Microsoft's tiny powerhouse. Punches well above its weight at 3.8B parameters, competitive with many 7B models on reasoning and coding benchmarks. Extremely fast inference. Ideal as a draft model or for resource-constrained setups.
View all Phi-4 Mini hardware options →About Apple M3 (8GB Unified)
Apple M3 (8GB Unified) has 8 GB at 100 GB/s. Available in MacBook Air 13" (2024), MacBook Air 15" (2024).
See all models Apple M3 (8GB Unified) can run →Estimate method: Conservative estimate anchored to m4-16gb with bandwidth scaling, quantization-size adjustment, and generation damping. 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.