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NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 GPU Requirements: VRAM & Cheapest GPU

NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 has about 561B parameters. See exactly how much GPU memory it needs at FP16, INT8, and INT4, and the cheapest GPU to run it, with live hourly pricing from 5+ data center partners.

561BParameters
305 GBMin VRAM
$4.76/hrCheapest
< 2 minDeploy
nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16
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561B paramstext-generationnemotron_h9.1K downloads106 likesupdated Jun 4, 2026

To run NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 for inference at FP16, you need roughly 1222 GB of VRAM. The cheapest fit on Spheron is 8x B200 192GB at about $21.44/hr. Quantize to INT4 to run it on a smaller, cheaper GPU.

GB VRAM REQUIRED
FP16INFERENCEBATCH 1CTX 4k

Estimated peak VRAM including weights, activations, and KV cache. Add 10% headroom for production traffic.

RANKCONFIGURATIONPER GPUTOTAL $/HR
  • 01
    8× B200 192GBCHEAPEST
    Blackwell · HBM3e
    $2.68/hr$21.44/hr
  • 02
    8× B300 288GB
    Blackwell Ultra · HBM3e
    $3.35/hr$26.80/hr

Live pricing aggregated from 5+ data center partners. Per-minute billing, no commitments.

VRAM required to run NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16

Estimated peak VRAM at context length 4,096 and batch size 1, including weights, activations, and KV cache. Quantizing to INT8 (Q8) or INT4 (Q4) cuts memory roughly in half and in quarter.

PrecisionInferenceLoRA fine-tuneFull fine-tune
FP161222 GB1833 GB4888 GB
INT8611 GB916 GB2444 GB
INT4305 GB458 GB1222 GB

Cheapest GPU to run NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16 by precision

FP16
VRAM required1222GB

Full precision. Best quality, highest memory.

Cheapest GPU
8x B200 192GB
Blackwell · HBM3e
$21.44/hr · $2.68/hr/gpu
8x B200 192GB on Spheron
INT8
VRAM required611GB

8-bit quantized. ~2x smaller, minimal quality loss.

Cheapest GPU
8x A100 80GB
Ampere · HBM2e
$9.52/hr · $1.19/hr/gpu
8x A100 80GB on Spheron
INT4
VRAM required305GB

4-bit quantized. ~4x smaller, runs on smaller GPUs.

Cheapest GPU
4x A100 80GB
Ampere · HBM2e
$4.76/hr · $1.19/hr/gpu
4x A100 80GB on Spheron

Inference vs fine-tuning NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16

InferenceWeights + KV cache
LoRA fine-tune~1.5×+ low-rank adapter
Full fine-tune~4×+ gradients + optimizer state

Inference only holds the model weights plus a KV cache, so it is the cheapest setup. LoRA fine-tuning adds a small adapter and roughly 50% more memory. Full fine-tuning holds gradients and optimizer state on top of the weights, which is about 4x the inference footprint, so it often needs multiple GPUs even when inference fits on one. For NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16, an on-demand B200 192GB instance covers inference and LoRA, while a full fine-tune needs several times that memory and often spans multiple GPUs. Check the live GPU pricing for current rates.

Deployment guideDeploy Nemotron 3 Super step by stepHands-on production setup, GPU configs, and benchmarks for NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16.Read guide

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