MicrosoftPhi-4 Mini on NVIDIA GeForce RTX 4060 Ti 16GB
Yes — RTX 4060 Ti 16GB runs Phi-4 Mini excellently at Q8_0 — 68 tok/s. 16 GB VRAM with plenty of headroom.
Model Size
3.82B
Device VRAM
16 GB
Bandwidth
288 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Phi-4 Mini on NVIDIA GeForce RTX 4060 Ti 16GB at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 68 tok/s | 65ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
Q8_0 fits with 11GB headroom. Good speed for 3.8B reasoning model.
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 4060 Ti 16GB
NVIDIA GeForce RTX 4060 Ti 16GB has 16 GB at 288 GB/s. Street price: $449.
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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.