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
| Component | Rate (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
- Negotiation loops: Two agents disagree on a handoff and iterate 50+ times before converging.
- Broadcast storms: One agent posts to all subscribers; each replies, triggering more posts.
- Orphaned conversations: Agents wait for a response that never comes, polling the board every 30 seconds.
FinOps controls
- Message budget per workflow: Hard cap on total board tokens per task ID.
- Depth limits: Max 3 agent-to-agent hops before human escalation.
- Model routing: Route coordination to Sol; reserve Astra for the final synthesis step only.
- 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.
Related
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