MicrosoftPhi-4 Mini on NVIDIA GeForce RTX 4080 Super
Yes — RTX 4080 Super runs Phi-4 Mini excellently at Q8_0 — 130 tok/s. 16 GB VRAM with plenty of headroom.
Model Size
3.82B
Device VRAM
16 GB
Bandwidth
736 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-4 Mini on NVIDIA GeForce RTX 4080 Super at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 130 tok/s | 33ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
736 GB/s. Phi-4 mini at full Q8 quality.
About Phi-4 Mini
Phi-4 Mini (3.82B) is a chat, coding, ai coding, reasoning model. Microsoft's tiny powerhouse. Punches well above its weight at 3.8B parameters, competitive with many 7B models on reasoning and coding benchmarks. Extremely fast inference. Ideal as a draft model or for resource-constrained setups.
View all Phi-4 Mini hardware options →About NVIDIA GeForce RTX 4080 Super
NVIDIA GeForce RTX 4080 Super has 16 GB at 736 GB/s. Street price: $979.
See all models NVIDIA GeForce RTX 4080 Super 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.