Can RTX 4070 12GB run Phi-4-reasoning?

NVIDIA · 12 GB GDDR6X · 504 GB/s bandwidth · Microsoft · 14.7B · model ctx up to 32K

Partly — Phi-4-reasoning at Q4 fits the RTX 4070 12GB (12 GB GDDR6X) at 4K context (≈ 10.56 GB) but not at the default 8K (≈ 12.03 GB needed). Use a shorter context or partial offload. Decode at Q4/8K: ≈ 62.0 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	Yes	21.8 est.
Q4	8K default	12.03 GB	No	62.0 est.
Q4	32K	20.84 GB	No	20.7 est.
FP16	4K	31.87 GB	No	2.4 est.
FP16	8K default	33.34 GB	No	2.2 est.
FP16	32K	42.16 GB	No	1.4 est.

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 4070 12GB VRAM
Q4	8.09 GB	2.94 GB	1 GB	12.03 GB	12 GB
FP16	29.4 GB	2.94 GB	1 GB	33.34 GB	12 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 4070 12GB

• Qwen3-0.6B — ≈400.9 tok/s Q4 est.
• gemma-3-1b-it — ≈320.7 tok/s Q4 est.
• Llama-3.2-1B-Instruct — ≈267.3 tok/s Q4 est.
• Llama-3.2-3B-Instruct — ≈160.7 tok/s Q4 measured
• Qwen3-1.7B — ≈160.4 tok/s Q4 est.
• Phi-4-mini-instruct — ≈84.4 tok/s Q4 est.
• Phi-4-mini-reasoning — ≈84.4 tok/s Q4 est.
• gemma-3-4b-it — ≈82.2 tok/s Q4 est.

All models on the RTX 4070 12GB →