MicrosoftPhi-4 Mini on NVIDIA GeForce RTX 4090
Yes — RTX 4090 runs Phi-4 Mini excellently at Q8_0 — 160 tok/s. 24 GB VRAM with plenty of headroom.
Model Size
3.82B
Device VRAM
24 GB
Bandwidth
1008 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-4 Mini on NVIDIA GeForce RTX 4090 at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 160 tok/s | 28ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
3.8B reasoning model flies on 4090. 19GB headroom.
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 4090
NVIDIA GeForce RTX 4090 has 24 GB at 1008 GB/s. Street price: $1,799.
See all models NVIDIA GeForce RTX 4090 can run →Builds with NVIDIA GeForce RTX 4090
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.