MicrosoftPhi-3 Mini 3.8B Instruct on NVIDIA GeForce RTX 4090
Yes — RTX 4090 runs Phi-3 Mini 3.8B Instruct excellently at Q8_0 — 130 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-3 Mini 3.8B Instruct 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 | 130 tok/s | 40ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
Overkill GPU for this model, but useful as a fast secondary model alongside larger ones.
About Phi-3 Mini 3.8B Instruct
Phi-3 Mini 3.8B Instruct (3.82B) is a chat, coding, reasoning model. Punches above its weight: a 3.8B model that rivals many 7B models on reasoning benchmarks. MIT license. Well suited for resource-constrained setups or as a fast secondary model.
View all Phi-3 Mini 3.8B Instruct 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: Community benchmarks. Reference hardware source: github.com (2026-01-15)
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.