OpenAI Lets Codex Route Smaller Tasks From Sol to Lower-Cost Luna Workers

OpenAI has added cross-model delegation to Codex Multi Agents v2, allowing GPT-5.6 Sol to direct a job while assigning bounded tasks to GPT-5.6 Luna. It creates a model hierarchy within a coding workflow: Sol handles decomposition and result assembly, while Luna takes contained work as the faster, lower-cost worker. The routing is limited to supported Codex models, rather than outside providers.

The design is narrower than a free-form agent swarm. Luna workers cannot message other agents or spawn more workers. Sol retains the orchestration tools, leaving the parent responsible for breaking down the job, supplying instructions, and collecting results.

That puts Luna in a role suited to clearly scoped execution, while Sol holds the wider plan. The handoff must stand on its own: a Luna worker without the parent conversation needs an initial instruction containing everything required to finish its assignment.

An opt-in route, not the new default

The feature becomes available after an app update, but developers must prompt Codex to use a different model. Without that instruction, it continues spawning workers with the parent model, reasoning setting, and context-forking behavior. A Sol session therefore still produces Sol workers by default.

The default is presented as the higher-performing mode in evaluations, but it runs more slowly and uses more tokens. Luna is the GPT-5.6 family’s most cost-efficient model and is positioned as its fastest, lowest-cost option. Cross-model routing offers a second mode built around specialization and explicit budgets.

Context is now a design constraint

For workers that do not need the parent conversation, the recommended setup is fork_turns: none and a complete opening prompt. Guidance also advises against running more than six to eight subagents because of reliability concerns. Those are operating recommendations, not enforced limits.

A missing worker tier becomes usable

The change resolves a prior routing gap: Multi Agents v2 had accepted Sol and Terra subagents while rejecting Luna as an unknown model. Earlier behavior also exposed a mismatch in which the runtime could accept model and reasoning-effort fields that were absent from the spawn-tool definition shown to the parent.

Developers can now select a model and reasoning effort task by task instead of making that choice for an entire session. The practical test is whether routine work can be isolated without stripping away the context needed to complete it correctly.