Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM — Hardware Requirements & GPU Compatibility
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2.5K downloads
26 likesSpecifications
- Publisher
- Ex0bit
- Parameters
- 30B
- Release Date
- 2026-01-23
- License
- Other
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How Much VRAM Does Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 66 GB | — | 60.00 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM?
BF16 · 66 GBElbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM (BF16) requires 66 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 86+ GB is recommended. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM?
BF16 · 66 GB5 devices with unified memory can run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Related Models
Frequently Asked Questions
- How much VRAM does Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM need?
Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM requires 66 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 30B × 16 bits ÷ 8 = 60 GB
KV Cache + Overhead ≈ 6 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF1666.0 GB- Can NVIDIA GeForce RTX 5090 run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM?
No — Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM requires at least 66 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM on a Mac?
Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM requires at least 66 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM locally?
Yes — Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM can run locally on consumer hardware. At BF16 quantization it needs 66 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM?
At BF16, Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM can reach ~44 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 66.0 × 0.55 = ~44 tok/s
Estimated speed at BF16 (66 GB)
AMD Instinct MI300X~44 tok/sNVIDIA H100 SXM~33 tok/sAMD Instinct MI250X~27 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM?
At BF16, the download is about 60.00 GB.
- Which GPUs can run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM?
No single consumer GPU has enough VRAM to run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM at BF16 (66 GB). Multi-GPU or professional hardware is required.
- Which devices can run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM?
5 devices with unified memory can run Elbaz NVIDIA Nemotron 3 Nano 30B A3B PRISM at BF16 (66 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), NVIDIA DGX A100 640GB. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.