NVIDIA Nemotron 3 Nano 30B A3B Base BF16 — Hardware Requirements & GPU Compatibility
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NVIDIA Nemotron 3 Nano 30B A3B Base BF16 is the foundation model version of the Nemotron 3 Nano 30B, offered in full BF16 precision. Unlike the chat-tuned variants, this base model hasn't been instruction-tuned, making it suitable for fine-tuning, research, or custom alignment workflows. At 31.6 billion total parameters with a mixture-of-experts architecture, the base model gives developers and researchers a strong starting point for building specialized applications. It retains all the architectural benefits of the MoE design while leaving the behavioral layer open for customization.
55.9K downloads
132 likesSpecifications
- Publisher
- NVIDIA
- Family
- Nemotron
- Parameters
- 31.6B
- Release Date
- 2025-12-03
- License
- Other
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How Much VRAM Does NVIDIA Nemotron 3 Nano 30B A3B Base BF16 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 14.8 GB | — | 13.42 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 16.9 GB | — | 15.39 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 20.8 GB | — | 18.95 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 24.8 GB | — | 22.50 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 28.7 GB | — | 26.05 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 34.7 GB | — | 31.58 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 69.5 GB | — | 63.16 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run NVIDIA Nemotron 3 Nano 30B A3B Base BF16?
Q4_K_M · 20.8 GBNVIDIA Nemotron 3 Nano 30B A3B Base BF16 (Q4_K_M) requires 20.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 28+ GB is recommended. 7 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run NVIDIA Nemotron 3 Nano 30B A3B Base BF16?
Q4_K_M · 20.8 GB41 devices with unified memory can run NVIDIA Nemotron 3 Nano 30B A3B Base BF16, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightBenchmarks
Benchmark details →Related Models
Frequently Asked Questions
- How much VRAM does NVIDIA Nemotron 3 Nano 30B A3B Base BF16 need?
NVIDIA Nemotron 3 Nano 30B A3B Base BF16 requires 20.8 GB of VRAM at Q4_K_M, or 69.5 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 31.6B × 4.8 bits ÷ 8 = 18.9 GB
KV Cache + Overhead ≈ 1.9 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M20.8 GB- Can NVIDIA GeForce RTX 4090 run NVIDIA Nemotron 3 Nano 30B A3B Base BF16?
Yes, at Q4_K_M (20.8 GB) or lower. Higher quantizations like Q5_K_M (24.8 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for NVIDIA Nemotron 3 Nano 30B A3B Base BF16?
For NVIDIA Nemotron 3 Nano 30B A3B Base BF16, Q4_K_M (20.8 GB) offers the best balance of quality and VRAM usage. Q5_K_M (24.8 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 14.8 GB.
VRAM requirement by quantization
Q2_K14.8 GBQ4_K_M ★20.8 GBQ5_K_M24.8 GBQ6_K28.7 GBQ8_034.7 GBBF1669.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run NVIDIA Nemotron 3 Nano 30B A3B Base BF16 on a Mac?
NVIDIA Nemotron 3 Nano 30B A3B Base BF16 requires at least 14.8 GB at Q2_K, 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 NVIDIA Nemotron 3 Nano 30B A3B Base BF16 locally?
Yes — NVIDIA Nemotron 3 Nano 30B A3B Base BF16 can run locally on consumer hardware. At Q4_K_M quantization it needs 20.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is NVIDIA Nemotron 3 Nano 30B A3B Base BF16?
At Q4_K_M, NVIDIA Nemotron 3 Nano 30B A3B Base BF16 can reach ~100 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~177 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 20.8 × 0.65 = ~331 tok/s
Estimated speed at Q4_K_M (20.8 GB)
~331 tok/s~177 tok/s~331 tok/s~307 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of NVIDIA Nemotron 3 Nano 30B A3B Base BF16?
At Q4_K_M, the download is about 18.95 GB. The full-precision BF16 version is 63.16 GB. The smallest option (Q2_K) is 13.42 GB.
- Which GPUs can run NVIDIA Nemotron 3 Nano 30B A3B Base BF16?
7 consumer GPUs can run NVIDIA Nemotron 3 Nano 30B A3B Base BF16 at Q4_K_M (20.8 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run NVIDIA Nemotron 3 Nano 30B A3B Base BF16?
41 devices with unified memory can run NVIDIA Nemotron 3 Nano 30B A3B Base BF16 at Q4_K_M (20.8 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.