How to use from
OpenClaw
Start the MLX server
# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "abenzerps/Nex-N2.5-mini-MLX-8bit"
Configure OpenClaw
# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "abenzerps/Nex-N2.5-mini-MLX-8bit" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Quick Links

Nex-N2.5-mini MLX — 8-bit

MLX 8-bit conversion of Nex-N2.5-mini, a sparse MoE language model for local inference, coding, reasoning, and long-context work. The source checkpoint supports a native context length of 262,144 tokens (256K).

Benchmarks

Nex-N2.5 benchmark results

Benchmark results reported by Nex AI for the original Nex-N2.5 checkpoint and its upstream evaluation setup.

Release

Format Quantization Size
MLX safetensors Affine 8-bit, group size 64 36.85 GB

This release contains the text-generation weights and tokenizer. It does not include MTP weights or a vision projector.

Usage

pip install -U mlx-lm
mlx_lm.generate \
  --model . \
  --prompt "Explain why reproducible builds matter." \
  --max-tokens 512

Source

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