Models
The six models an agent can run, what they cost relative to each other, and why there is no place to paste your own API key.
A model is chosen per agent. Hawi owns and secures the provider credentials, so OpenAI and Anthropic appear here as model choices rather than as connections you authorise — there is no personal-API-key field anywhere in the agent flow, and that is a design decision rather than a gap.
| Model | Provider | Identifier | Tier | Indicative credits | Positioning |
|---|---|---|---|---|---|
| 5.6 Sol | OpenAI (ChatGPT) | gpt-5.6-sol | Powerful | 18,400 | Strongest OpenAI option. Costs about 5x Luna. |
| 5.6 Terra | OpenAI (ChatGPT) | gpt-5.6-terra | Balanced | 9,200 | Balanced capability and cost. |
| 5.6 Luna | OpenAI (ChatGPT) | gpt-5.6-luna | Efficient | 3,680 | Fast and cheap. Good default for routine work. |
| Fable 5 | Anthropic | claude-fable-5 | Highest capability, highest credit use | 32,200 | Highest capability available. Burns credits fastest. |
| Opus 5 | Anthropic | claude-opus-5 | Premium | 16,100 | Deep reasoning. Costs about 4x Sonnet. |
| Sonnet 5 | Anthropic | claude-sonnet-5 | Advanced | 6,440 | Capable all-rounder. |
Picking one
The default is 5.6 Terra (gpt-5.6-terra), which is the balanced middle of the OpenAI range. Most routine operational work — classifying an inbound message, deciding whether stock cover has dropped below a threshold, drafting a supplier chase — does not need more than that, and the difference between the cheapest and the most capable model on this list is roughly nine times the credit burn per request.
- Routine, high-volume, well-bounded work: the efficient tier. Triage, classification, templated replies.
- Judgement against messy input: the balanced or advanced tier. Reading a supplier’s ambiguous email, reconciling a listing against a stock sheet.
- Work where being wrong is expensive and rare: the premium or highest tier. Reserve it for the agent that handles exceptions, not the one that handles volume.
Changing a model later
You can change an agent’s model at any time and it applies to the next run. If a stored selection points at a model that has since been retired, the product does not quietly route you somewhere else — it surfaces that the selection was migrated and asks you to pick again. Silently substituting a model changes behaviour and cost without anybody being told.