MicrosoftPhi-4 14B on NVIDIA GeForce RTX 4070 Ti 12GB
RTX 4070 Ti 12GB runs Phi-4 14B at Q3_K_M — 34 tok/s. Usable on 12 GB VRAM — see full quantization options below.
Model Size
14.7B
Device VRAM
12 GB
Bandwidth
504 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-4 14B on NVIDIA GeForce RTX 4070 Ti 12GB 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 | 34 tok/s | 175ms | ✓ Yes | Acceptable | estimated |
Notes
Q3_K_M
Q3_K_M fits. Q4 would need ~9.5GB, marginal. Compressed but usable.
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 GeForce RTX 4070 Ti 12GB
NVIDIA GeForce RTX 4070 Ti 12GB has 12 GB at 504 GB/s. Street price: $749.
See all models NVIDIA GeForce RTX 4070 Ti 12GB can run →Estimate method: 14.66B model. Q3_K_M fits with headroom. Reference hardware source: github.com (2026-03-15)
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.