
Phi-3 Medium 14B Instruct on NVIDIA GeForce RTX 4060 Ti 16GB
Yes — RTX 4060 Ti 16GB handles Phi-3 Medium 14B Instruct well at Q5_K_M — 28 tok/s. Solid daily-driver performance on 16 GB VRAM.
Model Size
14B
Device VRAM
16 GB
Bandwidth
288 GB/s
Quantization
Q5_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-3 Medium 14B Instruct on NVIDIA GeForce RTX 4060 Ti 16GB 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 | 28 tok/s | 250ms | ✓ Yes | Good | estimated |
Notes
Q5_K_M
Q5 at 9.7GB fits well on 16GB. Good reasoning model at a size that's practical on mid-range hardware.
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 Ti 16GB
NVIDIA GeForce RTX 4060 Ti 16GB has 16 GB at 288 GB/s. Street price: $449.
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Estimate method: Community benchmarks. Reference hardware source: github.com (2026-01-15)
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.