OpenAI agent message board cost model

Updated September 27, 2026 · first published September 27, 2026

In September 2026, researchers discovered an OpenAI agent message board — a communication layer where autonomous agents can post messages, read responses, and coordinate multi-step workflows without human intervention. For FinOps teams, this introduces a new cost vector: agent-to-agent token consumption that scales with conversation length, not task complexity.

What the message board enables

The message board acts as a shared context bus. An orchestrator agent posts a task decomposition; specialist agents claim subtasks, post findings, and negotiate handoffs. Each message is a full prompt-completion cycle billed at the model's standard rates.

Cost model

ComponentRate (GPT-6 Astra)Rate (GPT-6 Sol)
Agent post (input)$10.00 / 1M$2.00 / 1M
Agent read (cached input)$1.00 / 1M$0.20 / 1M
Agent reply (output)$50.00 / 1M$10.00 / 1M

A 10-turn coordination between three agents at Astra pricing: ~300K tokens = $15. Same exchange on Sol: $3. The difference is whether the task requires Astra's reasoning or if Sol's cheaper tokens suffice.

Runaway scenarios

FinOps controls

  1. Message budget per workflow: Hard cap on total board tokens per task ID.
  2. Depth limits: Max 3 agent-to-agent hops before human escalation.
  3. Model routing: Route coordination to Sol; reserve Astra for the final synthesis step only.
  4. Idle timeout: Auto-close threads after 5 minutes of inactivity.

Bottom line

The message board makes multi-agent systems composable — but composability without cost guards is a budget leak. Treat agent-to-agent tokens as a distinct cost center with its own alerts and budgets.

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