Can I Run GPT-OSS on NVIDIA GeForce RTX 4060 Ti 16GB?

Name: LLM Configurator — GPU VRAM Checker
Author: LLM Configurator

作者： Jakub Rusinowski · 最后更新： 2026年8月15日

Yes, comfortably — you'll have ~4.9 GB of headroom running GPT-OSS 20B at MXFP4 (11.1 GB, ~98 tok/s (est.)).

购买此硬件 NVIDIA GeForce RTX 4060 Ti 16GB — 16 GB VRAM · 165 W board power 立即云端部署 RunPod 上的 RTX 4090 — 低至 $0.34/小时 · 价格核实于 2026-07

或在 Vast.ai 比较，低至 $0.35/小时 (typical low · varies)

作为亚马逊联盟成员，我们从符合条件的购买中获得收入。云 GPU 链接为推荐链接——我们可能获得佣金，您无需额外付费。

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NVIDIA GeForce RTX 4060 Ti 16GB

16 GB VRAM · 165 W board power

2026年价格波动较大——请以当前商品页价格为准。

在亚马逊查看价格

NVIDIA GeForce RTX 4060 Ti 16GB Specs

VRAM	16 GB
Memory Bandwidth	288 GB/s

GPT-OSS 20B on the NVIDIA GeForce RTX 4060 Ti 16GB: VRAM by quantization

Quant	VRAM needed	Fits 16 GB?	Max context	Whole PC
F16	42.8 GB	✗ No	—	—
Q8_0	23.2 GB	✗ No	—	—
Q6_K	18.1 GB	✗ No	—	—
Q5_K_M	15.8 GB	✓ Yes	4K	—
Q4_K_M	13.6 GB	✓ Yes	32K	—
Q3_K_M	9.9 GB	✓ Yes	64K	—
Q2_K	7.9 GB	✓ Yes	128K	—

Assumes a 4K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 16 GB. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.

Context costs VRAM too. At MXFP4 on the NVIDIA GeForce RTX 4060 Ti 16GB: 8K 12.3 GB · 32K 13.5 GB · 128K 18.3 GB ✗. Past 128K it no longer fits 16 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.

No compatible GPU? GPT-OSS 20B on 16 GB of system RAM, CPU only: runs.