Can I Run GPT-OSS on NVIDIA GeForce RTX 5070 Ti?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 15 sierpnia 2026

Yes, comfortably — GPT-OSS 20B at MXFP4 needs 12.3 GB at 8K context (11.1 GB weights + 1.2 GB KV cache/overhead), leaving ~3.7 GB of the NVIDIA GeForce RTX 5070 Ti's 16 GB, at ~199 tok/s (est.).

See what else this hardware can run →

Kup ten sprzęt NVIDIA GeForce RTX 5070 Ti 16GB — 16 GB VRAM · 300 W board powerUruchom w chmurze RTX 4090 w RunPod — od $0.34/godz. · stawka sprawdzona 2026-07

lub porównaj w Vast.ai od $0.35/godz. (typical low · varies)

Jako partner Amazon zarabiamy na kwalifikujących się zakupach. Linki do chmurowych GPU są linkami polecającymi — możemy otrzymać prowizję bez dodatkowych kosztów dla Ciebie.

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.

NVIDIA GeForce RTX 5070 Ti 16GB
16 GB VRAM · 300 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

NVIDIA GeForce RTX 5070 Ti Specs

VRAM16 GB
Memory Bandwidth896 GB/s

GPT-OSS 20B on the NVIDIA GeForce RTX 5070 Ti: VRAM by quantization

QuantVRAM neededFits 16 GB?Max contextWhole PC
F1643 GB✗ No——
Q8_023.4 GB✗ No——
Q6_K18.3 GB✗ No——
Q5_K_M16 GB✗ No——
Q4_K_M13.8 GB✓ Yes32K—
Q3_K_M10.1 GB✓ Yes64K—
Q2_K8.1 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 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 5070 Ti: 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.

GPT-OSS Sizes That Fit the NVIDIA GeForce RTX 5070 Ti (at 8K context)

GPT-OSS 20BMXFP4 · 12.3 GB at 8K context · ~199 tok/s (est.)
Buy vs. rent GPT-OSS
Buy the GPU
~$749
NVIDIA GeForce RTX 5070 Ti · MSRP
Rent by the hour
from $0.34/hr
RTX 4090 (24 GB) class

At 2 hrs/day, buying (~$749) beats renting at $0.34/hr after about 3.1 years.

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RunPod $0.34/hr
Rent on RunPod →
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

Will GPT-OSS run on the NVIDIA GeForce RTX 5070 Ti?

Yes, comfortably — GPT-OSS 20B at MXFP4 needs 12.3 GB at 8K context (11.1 GB weights + 1.2 GB KV cache/overhead), leaving ~3.7 GB of the NVIDIA GeForce RTX 5070 Ti's 16 GB, at ~199 tok/s (est.).

Which GPT-OSS variant fits best on the NVIDIA GeForce RTX 5070 Ti?

GPT-OSS 20B at MXFP4 quantization needs 12.3 GB at 8K context (11.1 GB weights + 1.2 GB KV cache/overhead), estimated ~199 tokens/sec.

Every GPT-OSS size on the NVIDIA GeForce RTX 5070 Ti

SizeVRAM at 8KVerdictSpeed
GPT-OSS 120B71.9 GBDoes not fit—
GPT-OSS 20B12.3 GBRuns~199 tok/s

GPT-OSS on Other GPUs

Popular Models on the NVIDIA GeForce RTX 5070 Ti

VRAM Tier

Troubleshooting

Buying Guide

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