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/MiniCPM5-2B-MLX-6bit"
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/MiniCPM5-2B-MLX-6bit" \
  --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

MiniCPM5-2B MLX - 6-bit

MLX 6-bit conversion of OpenBMB/MiniCPM5-2B, a 2B dense Llama-based model for local deployment, coding, reasoning, long-context work, and tool use. The source checkpoint supports a native context length of 131,072 tokens (128K).

Benchmarks

MiniCPM5-2B evaluation results

MiniCPM5-2B capability radar

Benchmark results reported by OpenBMB for the original MiniCPM5-2B checkpoint.

Release

Format Quantization Size
MLX safetensors Affine 6-bit, group size 64 2.0 GB

The model is text-only. No vision projector or MTP files are included.

Usage

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

Source

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