Can RTX 5060 Ti 8GB run Qwen2.5-Coder-14B-Instruct?

NVIDIA · 8 GB GDDR7 · 448 GB/s bandwidth · Alibaba · 14.8B · model ctx up to 32K

No — Qwen2.5-Coder-14B-Instruct at Q4 needs ≈ 10.62 GB even at 4K context, beyond the RTX 5060 Ti 8GB's 8 GB GDDR7. It would only run with heavy CPU/disk offload. Decode at Q4/8K: ≈ 24.1 tok/s (estimated, batch 1). FP16 needs ≈ 33.56 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	10.62 GB	No	31.2 est.
Q4	8K default	12.1 GB	No	24.1 est.
Q4	32K	20.98 GB	No	8.0 est.
FP16	4K	32.08 GB	No	—
FP16	8K default	33.56 GB	No	—
FP16	32K	42.44 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 5060 Ti 8GB VRAM
Q4	8.14 GB	2.96 GB	1 GB	12.1 GB	8 GB
FP16	29.6 GB	2.96 GB	1 GB	33.56 GB	8 GB

Other GPUs that run Qwen2.5-Coder-14B-Instruct

• B200 192GB SXM — ≈344.0 tok/s Q4 est.
• MI300X 192GB — ≈227.9 tok/s Q4 est.
• H200 141GB SXM5 — ≈206.4 tok/s Q4 est.
• H100 80GB SXM5 — ≈144.0 tok/s Q4 est.
• Gaudi 3 128GB — ≈140.9 tok/s Q4 est.
• A100 80GB SXM4 — ≈87.7 tok/s Q4 est.
• RTX 5090 32GB — ≈77.1 tok/s Q4 est.
• RTX 4090 24GB — ≈43.3 tok/s Q4 est.

All GPUs for Qwen2.5-Coder-14B-Instruct →

Other models for the RTX 5060 Ti 8GB

• Qwen3-0.6B — ≈356.4 tok/s Q4 est.
• gemma-3-1b-it — ≈285.1 tok/s Q4 est.
• Llama-3.2-1B-Instruct — ≈237.6 tok/s Q4 est.
• Qwen3-1.7B — ≈142.5 tok/s Q4 est.
• Llama-3.2-3B-Instruct — ≈89.1 tok/s Q4 est.
• Phi-4-mini-instruct — ≈75.0 tok/s Q4 est.
• Phi-4-mini-reasoning — ≈75.0 tok/s Q4 est.
• gemma-3-4b-it — ≈73.1 tok/s Q4 est.

All models on the RTX 5060 Ti 8GB →