Can I Run Nemotron 3.5 on NVIDIA GeForce RTX 5090?
Written by Jakub Rusinowski · Last updated October 15, 2026
Yes, comfortably — 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 ~9.1 GB of the NVIDIA GeForce RTX 5090's 32 GB, at ~248 tok/s (est.), with room for up to 256K context.
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NVIDIA GeForce RTX 5090 Specs
| VRAM | 32 GB |
| Memory Bandwidth | 1792 GB/s |
Nemotron 3.5 Bolt 74B on the NVIDIA GeForce RTX 5090: VRAM by quantization
| Quant | VRAM needed | Fits 32 GB? | Max context | Whole PC |
|---|---|---|---|---|
| BF16 | 150.6 GB | ✗ No | — | — |
| IQ2_XXS QAD | 22.9 GB | ✓ Yes | 256K | — |
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 32 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 5090: 8K 22.9 GB · 32K 23.1 GB · 128K 23.9 GB. Every window this model publishes still fits 32 GB.
Nemotron 3.5 Sizes That Fit the NVIDIA GeForce RTX 5090 (at 8K context)
| Nemotron 3.5 Bolt 74B | IQ2_XXS QAD · 22.9 GB at 8K context · ~248 tok/s (est.) |
| Nemotron 3.5 Lightning 30B-A3B | Q4_K_M · 20.7 GB at 8K context · ~249 tok/s (est.) |
At 2 hrs/day, buying (~$1,999) beats renting at $0.34/hr after about 8.2 years.
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
Will Nemotron 3.5 run on the NVIDIA GeForce RTX 5090?
Yes, comfortably — 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 ~9.1 GB of the NVIDIA GeForce RTX 5090's 32 GB, at ~248 tok/s (est.), with room for up to 256K context.
Which Nemotron 3.5 variant fits best on the NVIDIA GeForce RTX 5090?
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 ~248 tokens/sec, up to 256K context.
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