Can I Run GPT-OSS on NVIDIA RTX PRO 6000 Blackwell?

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 15 sierpnia 2026

Yes, comfortably — GPT-OSS 120B at Q4_K_M needs 71.6 GB at 8K context (70.5 GB weights + 1.1 GB KV cache/overhead), leaving ~24.4 GB of the NVIDIA RTX PRO 6000 Blackwell's 96 GB, at ~228 tok/s (est.), with room for up to 128K context.

See what else this hardware can run →

Kup ten sprzęt NVIDIA RTX PRO 6000 Blackwell 96GB — 96 GB VRAM · 600 W board powerUruchom w chmurze NVIDIA A100 80GB w RunPod — od $1.39/godz. · stawka sprawdzona 2026-07

lub porównaj w Vast.ai od $0.77/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 RTX PRO 6000 Blackwell 96GB
96 GB VRAM · 600 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

NVIDIA RTX PRO 6000 Blackwell Specs

VRAM96 GB
Memory Bandwidth1792 GB/s

GPT-OSS 120B on the NVIDIA RTX PRO 6000 Blackwell: VRAM by quantization

QuantVRAM neededFits 96 GB?Max contextWhole PC
F16234.7 GB✗ No——
Q8_0125.2 GB✗ No——
Q6_K96.9 GB✗ No——
Q5_K_M83.9 GB✓ Yes128K—
Q4_K_M71.6 GB✓ Yes128K—
Q3_K_M50.9 GB✓ Yes128K—
Q2_K39.5 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 96 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 Q4_K_M on the NVIDIA RTX PRO 6000 Blackwell: 8K 71.6 GB · 32K 72.6 GB · 128K 76.2 GB. Every window this model publishes still fits 96 GB.

No compatible GPU? GPT-OSS 120B on 96 GB of system RAM, CPU only: runs, but it is tight.

GPT-OSS Sizes That Fit the NVIDIA RTX PRO 6000 Blackwell (at 8K context)

GPT-OSS 120BQ4_K_M · 71.6 GB at 8K context · ~228 tok/s (est.)
GPT-OSS 20BMXFP4 · 12.1 GB at 8K context · ~279 tok/s (est.)
Buy vs. rent GPT-OSS
Buy the GPU
~$8,565
NVIDIA RTX PRO 6000 Blackwell · MSRP
Rent by the hour
from $0.77/hr
A100 (80 GB) class

At 2 hrs/day, buying (~$8,565) beats renting at $0.77/hr after about 15.4 years.

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Vast.ai $0.77/hr · typical low · varies
Rent on Vast.ai →
RunPod $1.39/hr
Rent on RunPod →

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

FAQ

Is the NVIDIA RTX PRO 6000 Blackwell enough to run GPT-OSS locally?

Yes, comfortably — GPT-OSS 120B at Q4_K_M needs 71.6 GB at 8K context (70.5 GB weights + 1.1 GB KV cache/overhead), leaving ~24.4 GB of the NVIDIA RTX PRO 6000 Blackwell's 96 GB, at ~228 tok/s (est.), with room for up to 128K context.

What's the best GPT-OSS size for the NVIDIA RTX PRO 6000 Blackwell?

GPT-OSS 120B at Q4_K_M quantization needs 71.6 GB at 8K context (70.5 GB weights + 1.1 GB KV cache/overhead), estimated ~228 tokens/sec, up to 128K context.

Every GPT-OSS size on the NVIDIA RTX PRO 6000 Blackwell

SizeVRAM at 8KVerdictSpeed
GPT-OSS 120B71.6 GBRuns~228 tok/s
GPT-OSS 20B12.1 GBRuns~279 tok/s

GPT-OSS on Other GPUs

Popular Models on the NVIDIA RTX PRO 6000 Blackwell

VRAM Tier

Troubleshooting

Buying Guide

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