Nemotron 3 Nano Omni 30B A3B Reasoning BF16 — Hardware Requirements & GPU Compatibility
Reasoning
Nemotron 3 Nano Omni 30B A3B Reasoning BF16 is a 33.0B-parameter open language model from NVIDIA in the Nemotron family. At Q4_K_M it needs about 21.79 GB of VRAM — see which GPUs and Macs can run it below.
340.0K downloads
343 likesSpecifications
- Publisher
- NVIDIA
- Family
- Nemotron
- Parameters
- 33.0B
- Architecture
- NemotronH_Nano_Omni_Reasoning_V3
- Release Date
- 2026-04-20
- License
- Other
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How Much VRAM Does Nemotron 3 Nano Omni 30B A3B Reasoning BF16 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 15.4 GB | — | 14.03 GB | 2-bit quantization with K-quant improvements |
| Q3_K_M | 3.90 | 17.7 GB | — | 16.10 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 21.8 GB | — | 19.81 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 25.9 GB | — | 23.52 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 30.0 GB | — | 27.24 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 36.3 GB | — | 33.02 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
Q4_K_M · 21.8 GBNemotron 3 Nano Omni 30B A3B Reasoning BF16 (Q4_K_M) requires 21.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 29+ GB is recommended. 5 GPUs can run it, including NVIDIA GeForce RTX 5090.
All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).
Which Devices Can Run Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
Q4_K_M · 21.8 GB21 devices with unified memory can run Nemotron 3 Nano Omni 30B A3B Reasoning BF16, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightWhere to Download Nemotron 3 Nano Omni 30B A3B Reasoning BF16
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does Nemotron 3 Nano Omni 30B A3B Reasoning BF16 need?
Nemotron 3 Nano Omni 30B A3B Reasoning BF16 requires 21.8 GB of VRAM at Q4_K_M, or 72.6 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 33.0B × 4.8 bits ÷ 8 = 19.8 GB
KV Cache + Overhead ≈ 2 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M21.8 GB- Can NVIDIA GeForce RTX 4090 run Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
Yes, at Q4_K_M (21.8 GB) or lower. Higher quantizations like Q5_K_S (25.0 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
For Nemotron 3 Nano Omni 30B A3B Reasoning BF16, Q4_K_M (21.8 GB) offers the best balance of quality and VRAM usage. Q5_K_S (25.0 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 10.0 GB.
VRAM requirement by quantization
IQ2_XXS10.0 GBQ2_K15.4 GBQ4_K_S20.4 GBQ4_K_M ★21.8 GBQ5_K_M25.9 GBBF1672.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Nemotron 3 Nano Omni 30B A3B Reasoning BF16 on a Mac?
Nemotron 3 Nano Omni 30B A3B Reasoning BF16 requires at least 10.0 GB at IQ2_XXS, 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 Nemotron 3 Nano Omni 30B A3B Reasoning BF16 locally?
Yes — Nemotron 3 Nano Omni 30B A3B Reasoning BF16 can run locally on consumer hardware. At Q4_K_M quantization it needs 21.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
At Q4_K_M, Nemotron 3 Nano Omni 30B A3B Reasoning BF16 can reach ~134 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~30 tok/s. 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 ÷ 21.8 × 0.55 = ~134 tok/s
Estimated speed at Q4_K_M (21.8 GB)
~134 tok/s~30 tok/s~100 tok/s~83 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
At Q4_K_M, the download is about 19.81 GB. The full-precision BF16 version is 66.03 GB. The smallest option (IQ2_XXS) is 9.08 GB.
- Which GPUs can run Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
5 consumer GPUs can run Nemotron 3 Nano Omni 30B A3B Reasoning BF16 at Q4_K_M (21.8 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090.
- Which devices can run Nemotron 3 Nano Omni 30B A3B Reasoning BF16?
21 devices with unified memory can run Nemotron 3 Nano Omni 30B A3B Reasoning BF16 at Q4_K_M (21.8 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.