Nemotron Labs Audex 2B — Hardware Requirements & GPU Compatibility
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Nemotron Labs Audex 2B is a 2B-parameter open language model from NVIDIA in the Nemotron family. At BF16 it needs about 4.40 GB of VRAM — see which GPUs and Macs can run it below.
2.3K downloads
76 likesSpecifications
- Publisher
- NVIDIA
- Family
- Nemotron
- Parameters
- 2B
- Release Date
- 2026-07-06
- License
- Other
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HuggingFace
How Much VRAM Does Nemotron Labs Audex 2B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 4.4 GB | — | 4.00 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 Nemotron Labs Audex 2B?
BF16 · 4.4 GBNemotron Labs Audex 2B (BF16) requires 4.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 6+ GB is recommended. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Nemotron Labs Audex 2B?
BF16 · 4.4 GB59 devices with unified memory can run Nemotron Labs Audex 2B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPhone 17.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Nemotron Labs Audex 2B need?
Nemotron Labs Audex 2B requires 4.4 GB of VRAM at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 2B × 16 bits ÷ 8 = 4 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
BF164.4 GB- Can I run Nemotron Labs Audex 2B on a Mac?
Nemotron Labs Audex 2B requires at least 4.4 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 Nemotron Labs Audex 2B locally?
Yes — Nemotron Labs Audex 2B can run locally on consumer hardware. At BF16 quantization it needs 4.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Nemotron Labs Audex 2B?
At BF16, Nemotron Labs Audex 2B can reach ~1000 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~149 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 ÷ 4.4 × 0.65 = ~1182 tok/s
Estimated speed at BF16 (4.4 GB)
~1182 tok/s~149 tok/s~1182 tok/s~1000 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Nemotron Labs Audex 2B?
At BF16, the download is about 4.00 GB.
- Which GPUs can run Nemotron Labs Audex 2B?
50 consumer GPUs can run Nemotron Labs Audex 2B at BF16 (4.4 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 50 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Nemotron Labs Audex 2B?
59 devices with unified memory can run Nemotron Labs Audex 2B at BF16 (4.4 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, 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.