Nex-N2.5-mini-oQ5

Nex-N2.5-mini-oQ5

Unofficial MLX quantization of nex-agi/Nex-N2.5-mini for Apple Silicon. The upstream model is a multimodal mixture-of-experts model; this repository contains MLX safetensors, not GGUF or PyTorch weights. I am not affiliated with Nex AGI.

What is in this repository

The numbers above were read from the shipped config.json, model.safetensors.index.json and safetensors headers. The five shards contain 2,010 indexed tensors. The quantization recipe is recorded in config.json so a compatible MLX loader can reconstruct the per-module precision.

This conversion has not been benchmarked against the upstream BF16 model. The upstream benchmark figures on its model card are not results for these quantized weights. Quantization can change output quality, and memory use grows with context length and cache settings.

Usage

Download the model into your oMLX model directory:

hf download TokenAI-zer/Nex-N2.5-mini-oQ5 --local-dir ~/.omlx/models/Nex-N2.5-mini-oQ5
omlx serve --model-dir ~/.omlx/models --port 8000

Use the model ID Nex-N2.5-mini-oQ5 in oMLX. This architecture includes a vision tower, so use an MLX runtime with Qwen3.5 MoE multimodal support. The 262k context value is an architecture limit, not a promise that it will fit in memory.

License and attribution

The upstream repository declares Apache License 2.0. The published model includes the license text and a notice identifying the source and the quantization change. The upstream model and its reported evaluations belong to Nex AGI.

Citation

@misc{nex-n25-mini-oq5,
  title = {Nex-N2.5-mini-oQ5: MLX quantization of Nex-N2.5-mini},
  author = {TokenAI-zer},
  year = {2026},
  url = {https://huggingface.co/TokenAI-zer/Nex-N2.5-mini-oQ5},
  note = {Unofficial quantization of nex-agi/Nex-N2.5-mini}
}