Models & routing
Auto-routing across providers, quality bias, and pinning a specific model.
The model chip in the agent input footer controls which model answers. The default is auto: Mel routes each turn to the best model for the job across every configured provider — Anthropic, OpenAI, Gemini, Groq, DeepSeek, and Moonshot — without you thinking about it.
How auto routing works
auto is an instant heuristic router, not another model call. It classifies your turn in microseconds from cheap signals — prompt length, code and agentic cues, reasoning cues, context size — into a tier:
| Tier | Typical turn |
|---|---|
| Trivial | Quick questions, one-liners |
| Simple coding | Small edits, straightforward scripts |
| Complex coding | Multi-file changes, real builds |
| Reasoning | Hard analysis, tricky debugging |
| Huge context | Very large conversations or inputs |
Each tier maps to the best available model for it, so there's no routing latency before your answer starts streaming. The chip updates to auto → <model> once a turn routes, and the usage summary records the routed model plus a "why this model" line.
Bias: a ceiling, not a pin
In the picker's auto submenu you can bias the router:
- Responsive — balances quality, speed, and cost. The default.
- Cost-efficient — prefers the cheapest capable model; escalates only when it has to.
- Genius — escalates to the strongest model when the task is hard, while still using fast, cheap models for simple turns.
The bias raises or lowers the router's *ceiling* — it never pins one model for every turn. Genius does not mean "always the biggest model"; it means the hard turns are allowed to reach it.
Picking a model explicitly
Click the model chip (or type /model in the conversation) to open the picker. Models are grouped by provider, each with a brand monogram, and hovering a model shows its Model Specs card — intelligence, speed, and cost bars plus its context window. Select a model to pin it for the conversation; pick an auto tier to go back to routing. Your selection persists.
Reasoning levels
Models that support an adjustable reasoning effort (the OpenAI o-series) get a reasoning submenu — Low / Medium / High / XHigh. The level is only sent to models that actually support it.
Vision routing
When your turn includes image attachments, routing guarantees a model that can see them:
autoroutes to a vision-capable model, and any failover stays vision-capable — attachments are never silently dropped.- A pinned model without vision is upgraded to a vision model for that turn, announced in the transcript's router info.
- If no vision-capable provider is available, the turn fails with a clear error instead of ignoring your images.
For the wire-level routing contract, see Agent streaming.