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 "LiquidAI/LFM2.5-2.6B-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 "LiquidAI/LFM2.5-2.6B-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
Liquid AI
Try LFM • Docs • LEAP • Discord

LFM2.5-2.6B-MLX-8bit

MLX export of LFM2.5-2.6B for Apple Silicon inference.

LFM2.5-2.6B is a compact multilingual model built on LiquidAI's hybrid architecture, combining convolutional and attention layers for efficient long-context processing.

Model Details

Property Value
Parameters 2.6B
Precision 8-bit
Group Size 64
Size 2.67 GB
Context Length 131072

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate
from mlx_lm.sample_utils import make_sampler

model, tokenizer = load("LiquidAI/LFM2.5-2.6B-MLX-8bit")

response = generate(
    model,
    tokenizer,
    prompt="The capital of France is",
    max_tokens=100,
    sampler=make_sampler(temp=0.7),
    verbose=True,
)

Other Precisions

License

This model is released under the LFM 1.0 License.

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8-bit

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