MicrosoftPhi-4 14B on NVIDIA RTX 4070 Laptop (80-115W)
RTX 4070 Laptop (80-115W) runs Phi-4 14B at Q3_K_M — 13 tok/s. Usable on 8 GB VRAM — see full quantization options below.
Model Size
14.7B
Device VRAM
8 GB
Bandwidth
256 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-4 14B on NVIDIA RTX 4070 Laptop (80-115W) at Q3_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | 13 tok/s | 486ms | ✓ Yes | Acceptable | estimated |
Notes
Q3_K_M
Sustained post-thermal-throttle performance. TDP-capped laptop variant.
About Phi-4 14B
Phi-4 14B (14.7B) is a reasoning, coding, chat model. Microsoft's efficient reasoning and coding model with high performance per parameter.
View all Phi-4 14B hardware options →About NVIDIA RTX 4070 Laptop (80-115W)
NVIDIA RTX 4070 Laptop (80-115W) has 8 GB at 256 GB/s. Street price: $0.
See all models NVIDIA RTX 4070 Laptop (80-115W) 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.