Can RTX 4060 Ti 8GB run Phi-4-reasoning?

NVIDIA · 8 GB GDDR6 · 288 GB/s bandwidth · Microsoft · 14.7B · model ctx up to 32K

No — Phi-4-reasoning at Q4 needs ≈ 10.56 GB even at 4K context, beyond the RTX 4060 Ti 8GB's 8 GB GDDR6. It would only run with heavy CPU/disk offload. Decode at Q4/8K: ≈ 15.8 tok/s (estimated, batch 1). FP16 needs ≈ 33.34 GB — does not fit on this card. 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	10.56 GB	No	20.4 est.
Q4	8K default	12.03 GB	No	15.8 est.
Q4	32K	20.84 GB	No	5.2 est.
FP16	4K	31.87 GB	No	0.6 est.
FP16	8K default	33.34 GB	No	—
FP16	32K	42.16 GB	No	—

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).

VRAM breakdown at 8K context

Quant	Weights	KV cache	Overhead	Total needed	RTX 4060 Ti 8GB VRAM
Q4	8.09 GB	2.94 GB	1 GB	12.03 GB	8 GB
FP16	29.4 GB	2.94 GB	1 GB	33.34 GB	8 GB

Other GPUs that run Phi-4-reasoning

• B200 192GB SXM — ≈346.3 tok/s Q4 est.
• MI300X 192GB — ≈229.4 tok/s Q4 est.
• H200 141GB SXM5 — ≈207.8 tok/s Q4 est.
• H100 80GB SXM5 — ≈145.0 tok/s Q4 est.
• Gaudi 3 128GB — ≈141.8 tok/s Q4 est.
• A100 80GB SXM4 — ≈88.3 tok/s Q4 est.
• RTX 5090 32GB — ≈77.6 tok/s Q4 est.
• RTX 4090 24GB — ≈43.6 tok/s Q4 est.

All GPUs for Phi-4-reasoning →

Other models for the RTX 4060 Ti 8GB

• Qwen3-0.6B — ≈229.1 tok/s Q4 est.
• gemma-3-1b-it — ≈183.3 tok/s Q4 est.
• Llama-3.2-1B-Instruct — ≈152.7 tok/s Q4 est.
• Qwen3-1.7B — ≈91.6 tok/s Q4 est.
• Llama-3.2-3B-Instruct — ≈57.3 tok/s Q4 est.
• Phi-4-mini-instruct — ≈48.2 tok/s Q4 est.
• Phi-4-mini-reasoning — ≈48.2 tok/s Q4 est.
• gemma-3-4b-it — ≈47.0 tok/s Q4 est.

All models on the RTX 4060 Ti 8GB →