--- language: en library_name: mlx tags: - quantized - mlx base_model: - nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 pipeline_tag: text-generation --- **See NVIDIA-Nemotron-3-Super-120B-A12B MLX in action - [demonstration video](https://youtu.be/MzeRCbnOg9Q)** #### Tested on a M3 Ultra 512GB RAM using [Inferencer app v1.10.6](https://inferencer.com) - Single inference ~49.6 tokens/s @ 1000 tokens - Batched inference ~ total tokens/s across five inferences - Memory usage: ~67 GiB

q4.5bit quant targets 96GB RAM devices and typically achieves 91.65% accuracy in our coding test

QuantizationPerplexityToken AccuracyMissed Divergence
q3.5168.043.45%72.57%
q4.51.3359391.65%27.61%
q4.81.2812593.75%21.15%
q5.51.2343795.05%17.28%
q6.51.2187596.95%12.03%
q8.51.2109397.55%10.50%
q91.2109397.55%10.50%
Base1.20312100.0%0.000%
##### Quantized with a modified version of [MLX](https://github.com/ml-explore/mlx) ##### For more details see [demonstration video](https://youtu.be/MzeRCbnOg9Q) or visit [NVIDIA-Nemotron-3-Super-120B-A12B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16). ## Disclaimer We are not the creator, originator, or owner of any model listed. Each model is created and provided by third parties. Models may not always be accurate or contextually appropriate. You are responsible for verifying the information before making important decisions. We are not liable for any damages, losses, or issues arising from its use, including data loss or inaccuracies in AI-generated content.