MicrosoftPhi-3 Medium 14B Instruct on NVIDIA GeForce RTX 3080 10GB
RTX 3080 10GB runs Phi-3 Medium 14B Instruct at Q3_K_M — 32 tok/s. Usable on 10 GB VRAM — see full quantization options below.
Model Size
14B
Device VRAM
10 GB
Bandwidth
760 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 3080 10GB 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 | 32 tok/s | 200ms | ✓ Yes | Acceptable | estimated |
Notes
Q3_K_M
14B at Q3_K_M fits in 10GB. Tight but usable. Bandwidth helps.
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 3080 10GB
NVIDIA GeForce RTX 3080 10GB has 10 GB at 760 GB/s. Street price: $399.
See all models NVIDIA GeForce RTX 3080 10GB 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.