Can I Run Nemotron 3.5 on NVIDIA GeForce RTX 4090?

Written by Jakub Rusinowski · Last updated October 15, 2026

Yes, but it's tight — Nemotron 3.5 Bolt 74B at IQ2_XXS QAD needs 22.9 GB at 8K context (22 GB weights + 0.9 GB KV cache/overhead), leaving ~1.1 GB of the NVIDIA GeForce RTX 4090's 24 GB, at ~194 tok/s (est.), with room for up to 128K context.

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NVIDIA GeForce RTX 4090 24GB
24 GB VRAM · 450 W board power
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NVIDIA GeForce RTX 4090 Specs

VRAM24 GB
Memory Bandwidth1008 GB/s

Nemotron 3.5 Bolt 74B on the NVIDIA GeForce RTX 4090: VRAM by quantization

QuantVRAM neededFits 24 GB?Max contextWhole PC
BF16150.6 GB✗ No——
IQ2_XXS QAD22.9 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 IQ2_XXS QAD on the NVIDIA GeForce RTX 4090: 8K 22.9 GB · 32K 23.1 GB · 128K 23.9 GB. Every window this model publishes still fits 24 GB.

Nemotron 3.5 Sizes That Fit the NVIDIA GeForce RTX 4090 (at 8K context)

Nemotron 3.5 Bolt 74BIQ2_XXS QAD · 22.9 GB at 8K context · ~194 tok/s (est.)
Nemotron 3.5 Lightning 30B-A3BQ4_K_M · 20.7 GB at 8K context · ~195 tok/s (est.)
Buy vs. rent Nemotron 3.5
Buy the GPU
~$1,599
NVIDIA GeForce RTX 4090 · MSRP
Rent by the hour
from $0.34/hr
RTX 4090 (24 GB) class

At 2 hrs/day, buying (~$1,599) beats renting at $0.34/hr after about 6.5 years.

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FAQ

Nemotron 3.5 on the NVIDIA GeForce RTX 4090 — does it fit?

Yes, but it's tight — Nemotron 3.5 Bolt 74B at IQ2_XXS QAD needs 22.9 GB at 8K context (22 GB weights + 0.9 GB KV cache/overhead), leaving ~1.1 GB of the NVIDIA GeForce RTX 4090's 24 GB, at ~194 tok/s (est.), with room for up to 128K context.

Which Nemotron 3.5 variant fits best on the NVIDIA GeForce RTX 4090?

Nemotron 3.5 Bolt 74B at IQ2_XXS QAD quantization needs 22.9 GB at 8K context (22 GB weights + 0.9 GB KV cache/overhead), estimated ~194 tokens/sec, up to 128K context.

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