Fits comfortably
Running Phi-3.5 Mini Instruct on NVIDIA GeForce RTX 3080 16GB (Mobile)
NVIDIA GeForce RTX 3080 16GB (Mobile) runs Phi-3.5 Mini Instruct comfortably at Q8_0 with 11 GB of headroom for context.
Model size
3.8B params
Phi-3.5 Mini Instruct →Memory available
Recommended quant
Q8_0
Highest quality that fits
Quick start with Ollama
1. Install
ollama pull phi3.5:3.8b2. Run
ollama run phi3.5:3.8bDefault quant in Ollama is Q4_K_M. To use a different quant, append it: phi3.5:3.8b-q5_K_M.
Variants and what fits
| Quantization | File size | VRAM required | Fits on NVIDIA GeForce RTX 3080 16GB (Mobile)? |
|---|---|---|---|
| Q4_K_M | 2.4 GB | 4 GB | Yes |
| Q8_0 | 4.1 GB | 5 GB | Yes |
Real benchmarks
Frequently asked
Can NVIDIA GeForce RTX 3080 16GB (Mobile) run Phi-3.5 Mini Instruct?
NVIDIA GeForce RTX 3080 16GB (Mobile) runs Phi-3.5 Mini Instruct comfortably at Q8_0 with 11 GB of headroom for context.
What quantization should I use?
Q8_0 is the highest-quality variant of Phi-3.5 Mini Instruct that fits in 16 GB VRAM. Lower-bit quants will be smaller but lose some quality.
How fast will it be?
Measured at 155.4 tok/s on this combination in our testing.
See also: Phi-3.5 Mini Instruct, NVIDIA GeForce RTX 3080 16GB (Mobile), all benchmarks.
Reviewed by RunLocalAI Editorial. See our editorial policy.