MicrosoftPhi-3 Medium 14B Instruct on NVIDIA GeForce RTX 4060 8GB
RTX 4060 8GB runs Phi-3 Medium 14B Instruct at Q3_K_M — 20 tok/s due to limited memory bandwidth. Slow but functional — see all options below.
Model Size
14B
Device VRAM
8 GB
Bandwidth
272 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-3 Medium 14B Instruct on NVIDIA GeForce RTX 4060 8GB 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 | 20 tok/s | 320ms | ✓ Yes | Marginal | estimated |
Notes
Q3_K_M
14B model. Q3_K_M barely fits. Quality loss at Q3.
About Phi-3 Medium 14B Instruct
Phi-3 Medium 14B Instruct (14B) is a chat, coding, reasoning, multi-purpose model. 14B model with capable reasoning and coding performance. Fits comfortably on 16 GB GPUs at Q4 and excels at structured output tasks. MIT license makes it attractive for commercial use.
View all Phi-3 Medium 14B 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: 14B model. Q3_K_M ~7.5GB fits in 8GB. 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.