NVIDIA · 24 GB GDDR6X · 1008 GB/s bandwidth ·
Microsoft · 3.8B · model ctx up to 128K
Yes — the RTX 4090 24GB (24 GB GDDR6X) can run Phi-4-mini-instruct. At Q4 with the default 8K context it needs ≈ 3.85 GB VRAM (weights 2.09 GB + KV cache 0.76 GB + 1 GB runtime overhead), which fits within 24 GB. Decode at Q4/8K: ≈ 168.8 tok/s (estimated, batch 1). FP16 (≈ 9.36 GB) also fits, at ≈ 46.4 tok/s (estimated). Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.
Fit & speed by quant and context
Quant
Context
VRAM needed
Fits?
tok/s (decode)
Q4
4K
3.47 GB
Yes
168.8est.
Q4
8K default
3.85 GB
Yes
168.8est.
Q4
32K
6.13 GB
Yes
168.8est.
FP16
4K
8.98 GB
Yes
46.4est.
FP16
8K default
9.36 GB
Yes
46.4est.
FP16
32K
11.64 GB
Yes
46.4est.
Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured
anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s
means the model is far beyond this card (offload-only territory).