Fits comfortably
Running Phi-4 Reasoning 14B on NVIDIA GeForce RTX 3080 16GB (Mobile)
NVIDIA GeForce RTX 3080 16GB (Mobile) runs Phi-4 Reasoning 14B comfortably at Q4_K_M with 5 GB of headroom for context.
Model size
14B params
Phi-4 Reasoning 14B →Memory available
Recommended quant
Q4_K_M
Highest quality that fits
Quick start with Ollama
1. Install
ollama pull phi4-reasoning:14b2. Run
ollama run phi4-reasoning:14bDefault quant in Ollama is Q4_K_M. To use a different quant, append it: phi4-reasoning:14b-q5_K_M.
Variants and what fits
| Quantization | File size | VRAM required | Fits on NVIDIA GeForce RTX 3080 16GB (Mobile)? |
|---|---|---|---|
| Q4_K_M | 8.4 GB | 11 GB | Yes |
Real benchmarks
Frequently asked
Can NVIDIA GeForce RTX 3080 16GB (Mobile) run Phi-4 Reasoning 14B?
NVIDIA GeForce RTX 3080 16GB (Mobile) runs Phi-4 Reasoning 14B comfortably at Q4_K_M with 5 GB of headroom for context.
What quantization should I use?
Q4_K_M is the highest-quality variant of Phi-4 Reasoning 14B that fits in 16 GB VRAM. Lower-bit quants will be smaller but lose some quality.
How fast will it be?
Measured at 40.4 tok/s on this combination in our testing.
See also: Phi-4 Reasoning 14B, NVIDIA GeForce RTX 3080 16GB (Mobile), all benchmarks.
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