MicrosoftPhi-3 Mini 3.8B Instruct on NVIDIA GeForce RTX 4060 8GB
Yes — RTX 4060 8GB runs Phi-3 Mini 3.8B Instruct excellently at Q5_K_M — 52 tok/s. 8 GB VRAM with plenty of headroom.
Model Size
3.82B
Device VRAM
8 GB
Bandwidth
272 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-3 Mini 3.8B Instruct on NVIDIA GeForce RTX 4060 8GB at Q5_K_M. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q5_K_M | 52 tok/s | 130ms | ✓ Yes | Excellent | estimated |
Notes
Q5_K_M
3.82B model. Q5_K_M 3.0GB fits easily. Well suited for 8 GB.
About Phi-3 Mini 3.8B Instruct
Phi-3 Mini 3.8B Instruct (3.82B) is a chat, coding, reasoning model. Punches above its weight: a 3.8B model that rivals many 7B models on reasoning benchmarks. MIT license. Well suited for resource-constrained setups or as a fast secondary model.
View all Phi-3 Mini 3.8B Instruct hardware options →About NVIDIA GeForce RTX 4060 8GB
NVIDIA GeForce RTX 4060 8GB has 8 GB at 272 GB/s. Street price: $289.
See all models NVIDIA GeForce RTX 4060 8GB can run →Estimate method: Performance estimates based on model size and device bandwidth. 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.