MicrosoftPhi-4 Mini on NVIDIA RTX 4080 Laptop (120-150W)
Yes — RTX 4080 Laptop (120-150W) runs Phi-4 Mini excellently at Q8_0 — 57 tok/s. 12 GB VRAM with plenty of headroom.
Model Size
3.82B
Device VRAM
12 GB
Bandwidth
384 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-4 Mini on NVIDIA RTX 4080 Laptop (120-150W) at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 57 tok/s | 107ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
Sustained post-thermal-throttle performance. TDP-capped laptop variant.
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 NVIDIA RTX 4080 Laptop (120-150W)
NVIDIA RTX 4080 Laptop (120-150W) has 12 GB at 384 GB/s. Street price: $0.
See all models NVIDIA RTX 4080 Laptop (120-150W) can run →Estimate method: Community laptop benchmarks and thermal throttle reports. Reference hardware source: reddit.com (2026-03-14)
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.