Can RTX 5060 Ti 8GB run DeepSeek-R1-0528-Qwen3-8B-layer-mix-bpw-3.8-mlx?

NVIDIA · 8 GB GDDR7 · 448 GB/s bandwidth · GreenBitAI · 2.3B · model ctx up to NoneK

CUDA

Yes — the RTX 5060 Ti 8GB (8 GB GDDR7) can run DeepSeek-R1-0528-Qwen3-8B-layer-mix-bpw-3.8-mlx. At Q4 with the default 8K context it needs ≈ 2.72 GB VRAM (weights 1.26 GB + KV cache 0.46 GB + 1 GB runtime overhead), which fits within 8 GB. Decode at Q4/8K: ≈ 124.0 tok/s (estimated, batch 1). FP16 (≈ 6.06 GB) also fits, at ≈ 34.1 tok/s (estimated). Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology. Buy RTX 5060 Ti 8GB on Amazon →

Fit & speed by quant and context

Quant	Context	VRAM needed	Fits?	tok/s (decode)
Q4	4K	2.5 GB	Yes	124.0 ± est.
Q4	8K default	2.72 GB	Yes	124.0 ± est.
Q4	32K	4.1 GB	Yes	124.0 ± est.
FP16	4K	5.83 GB	Yes	34.1 ± est.
FP16	8K default	6.06 GB	Yes	34.1 ± est.
FP16	32K	7.44 GB	Yes	34.1 ± 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 5060 Ti 8GB VRAM
Q4	1.26 GB	0.46 GB	1 GB	2.72 GB	8 GB
FP16	4.6 GB	0.46 GB	1 GB	6.06 GB	8 GB

Other GPUs that run DeepSeek-R1-0528-Qwen3-8B-layer-mix-bpw-3.8-mlx

• B200 192GB SXM — ≈2213.4 tok/s Q4 est.
• MI300X 192GB — ≈1466.4 tok/s Q4 est.
• H200 141GB SXM5 — ≈1328.1 tok/s Q4 est.
• H100 80GB SXM5 — ≈926.9 tok/s Q4 est.
• Gaudi 3 128GB — ≈906.4 tok/s Q4 est.
• A100 80GB SXM4 — ≈564.2 tok/s Q4 est.
• RTX 5090 32GB — ≈495.8 tok/s Q4 est.
• RTX 4090 24GB — ≈278.9 tok/s Q4 est.

All GPUs for DeepSeek-R1-0528-Qwen3-8B-layer-mix-bpw-3.8-mlx →

Other models for the RTX 5060 Ti 8GB

• MiniCPM5-1B — ≈264.0 tok/s Q4 est.
• Qwen3.5-2B — ≈142.5 tok/s Q4 est.
• Llama-3.2-3B-Instruct — ≈89.1 tok/s Q4 est.
• Qwen3-4B-Instruct-2507 — ≈71.3 tok/s Q4 est.
• NVIDIA-Nemotron-3-Nano-4B-BF16 — ≈71.3 tok/s Q4 est.
• Qwen3-4B-Thinking-2507 — ≈71.3 tok/s Q4 est.
• gemma-4-E2B-it — ≈55.9 tok/s Q4 est.
• Mistral-7B-Instruct-v0.3 — ≈39.6 tok/s Q4 est.

All models on the RTX 5060 Ti 8GB →