Can I Run GPT-OSS on NVIDIA GeForce RTX 3090?

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

Yes, comfortably — GPT-OSS 20B at MXFP4 needs 12.1 GB at 8K context (11.1 GB weights + 1 GB KV cache/overhead), leaving ~11.9 GB of the NVIDIA GeForce RTX 3090's 24 GB, at ~174 tok/s (est.).

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NVIDIA GeForce RTX 3090 24GB
24 GB VRAM · 350 W board power
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NVIDIA GeForce RTX 3090 Specs

VRAM24 GB
Memory Bandwidth936 GB/s

GPT-OSS 20B on the NVIDIA GeForce RTX 3090: VRAM by quantization

QuantVRAM neededFits 24 GB?Max contextWhole PC
F1642.8 GB✗ No——
Q8_023.2 GB✓ Yes32K—
Q6_K18.2 GB✓ Yes128K—
Q5_K_M15.8 GB✓ Yes128K—
Q4_K_M13.6 GB✓ Yes128K—
Q3_K_M9.9 GB✓ Yes128K—
Q2_K7.9 GB✓ Yes128K—

Assumes an 8K-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 24 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 3090: 8K 12.1 GB · 32K 12.7 GB · 128K 15.1 GB. Every window this model publishes still fits 24 GB.

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

GPT-OSS Sizes That Fit the NVIDIA GeForce RTX 3090 (at 8K context)

GPT-OSS 20BMXFP4 · 12.1 GB at 8K context · ~174 tok/s (est.)
Buy vs. rent GPT-OSS
Buy the GPU
~$1,499
NVIDIA GeForce RTX 3090 · MSRP
Rent by the hour
from $0.34/hr
RTX 4090 (24 GB) class

At 2 hrs/day, buying (~$1,499) beats renting at $0.34/hr after about 6.1 years.

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RunPod $0.34/hr
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Vast.ai $0.35/hr · typical low · varies
Rent on Vast.ai →

Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.

FAQ

Can I run GPT-OSS on the NVIDIA GeForce RTX 3090?

Yes, comfortably — GPT-OSS 20B at MXFP4 needs 12.1 GB at 8K context (11.1 GB weights + 1 GB KV cache/overhead), leaving ~11.9 GB of the NVIDIA GeForce RTX 3090's 24 GB, at ~174 tok/s (est.).

What's the best GPT-OSS size for the NVIDIA GeForce RTX 3090?

GPT-OSS 20B at MXFP4 quantization needs 12.1 GB at 8K context (11.1 GB weights + 1 GB KV cache/overhead), estimated ~174 tokens/sec.

Every GPT-OSS size on the NVIDIA GeForce RTX 3090

SizeVRAM at 8KVerdictSpeed
GPT-OSS 120B71.6 GBDoes not fit—
GPT-OSS 20B12.1 GBRuns~174 tok/s

GPT-OSS on Other GPUs

Popular Models on the NVIDIA GeForce RTX 3090

VRAM Tier

Troubleshooting

Buying Guide

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