Cactus Hybrid
Cloud accuracy without the cloud cost
Post-trained models that know when they're wrong and request help from the cloud.
Cactus routes agent commands based on complexity: on-device for simple tasks, cloud for complex operations.
Set the thermostat to 72 degrees
The smallest Gemma 4 model matches Gemini 3.1 Flash-Lite on a given task by handing off the following share of queries:
Router in the Weights
We post-train a router inside the model weights, which reads internal activations and calculates a confidence score for each task.
Runs on Your Existing Stack
Run natively with the Cactus Engine, as well as llama.cpp, MLX, or Transformers.
Beyond Gemma
The post-training recipe extends to other models — as well as to your proprietary weights. Talk to us.
No compromise
Get the best of both on-device and cloud.
Ready to get started?
Add hybrid inference to your app in minutes. Free to start, scales with you.