AI Models in HALO

HALO is built on a multi-model architecture. Rather than relying on a single AI model for everything, you can now configure which model powers each part of your setup — optimising for performance, vendor preference or speed depending on the task.

This article covers model configuration across HALO's core features: agents, tools, and guardrails. Behind the scenes, HALO uses additional models for internal functions like automatic translation and platform-level safety, but those aren't covered here.

Default models

The default agent model has been updated to GPT 5.4 — an upgrade from the previous default of GPT 5.1. GPT 5.4 brings improved reasoning and instruction-following, making it better suited for complex agentic workflows.

For tools and guardrails, Claude Haiku 4.5 remains the default — it is fast, consistent, and well-suited to structured, high-volume tasks.

Configuring models per component

You can override the default model at each of the following components:

• Agent — set in Agent Settings, under Model Parameters

• LLM Interaction step — set within the step configuration in the Tool Editor

• Agentic Interaction step — set within the step configuration in the Tool Editor

• Custom Guardrail — set per agent within Agent Settings

This gives you fine-grained control: you might use a more capable model for a complex reasoning agent while keeping Haiku for high-frequency tool steps where speed matters more.

For the current list of available models, check the model selector in HALO Studio — the available options are updated as new models are added to the platform.

Model characteristics

GPT 5.4 is adaptive and conversational — it handles open-ended tasks and ambiguity well, and is purpose-built for agentic work. It follows complex instructions without needing rigid prompt structures and produces responses that feel natural.

Claude Haiku 4.5 is fast and precise — it excels at structured, well-defined tasks where consistency matters. It is ideal for classification, decision-making, and any high-volume operation where latency matters.

What this means for you

You can now match the model to the task rather than applying a single model across your entire setup. Use a powerful reasoning model where it matters, and a fast, efficient model where throughput and consistency are the priority.

As the AI landscape evolves, so will HALO. Our architecture is designed to adopt new models as they emerge — ensuring you're always building on a strong foundation.