Can RTX 4060 8GB run DeepSeek-R1-Distill-Qwen-32B?

NVIDIA · 8 GB GDDR6 · 272 GB/s bandwidth · DeepSeek · 32.8B · model ctx up to 128K

No — DeepSeek-R1-Distill-Qwen-32B at Q4 needs ≈ 22.32 GB even at 4K context, beyond the RTX 4060 8GB's 8 GB GDDR6. It would only run with heavy CPU/disk offload. Decode at Q4/8K: ≈ 1.5 tok/s (estimated, batch 1). FP16 needs ≈ 73.16 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	22.32 GB	No	1.9 est.
Q4	8K default	25.6 GB	No	1.5 est.
Q4	32K	45.28 GB	No	—
FP16	4K	69.88 GB	No	—
FP16	8K default	73.16 GB	No	—
FP16	32K	92.84 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 8GB VRAM
Q4	18.04 GB	6.56 GB	1 GB	25.6 GB	8 GB
FP16	65.6 GB	6.56 GB	1 GB	73.16 GB	8 GB

Other GPUs that run DeepSeek-R1-Distill-Qwen-32B

• B200 192GB SXM — ≈155.2 tok/s Q4 est.
• MI300X 192GB — ≈102.8 tok/s Q4 est.
• H200 141GB SXM5 — ≈93.1 tok/s Q4 est.
• H100 80GB SXM5 — ≈65.0 tok/s Q4 est.
• Gaudi 3 128GB — ≈63.6 tok/s Q4 est.
• A100 80GB SXM4 — ≈39.6 tok/s Q4 est.
• RTX 5090 32GB — ≈34.8 tok/s Q4 est.
• RTX 6000 Ada 48GB — ≈18.6 tok/s Q4 est.

All GPUs for DeepSeek-R1-Distill-Qwen-32B →

Other models for the RTX 4060 8GB

• Qwen3-0.6B — ≈216.4 tok/s Q4 est.
• gemma-3-1b-it — ≈173.1 tok/s Q4 est.
• Llama-3.2-1B-Instruct — ≈144.2 tok/s Q4 est.
• Qwen3-1.7B — ≈86.5 tok/s Q4 est.
• Llama-3.2-3B-Instruct — ≈54.1 tok/s Q4 est.
• Phi-4-mini-instruct — ≈45.6 tok/s Q4 est.
• Phi-4-mini-reasoning — ≈45.6 tok/s Q4 est.
• gemma-3-4b-it — ≈44.4 tok/s Q4 est.

All models on the RTX 4060 8GB →