# IBM uses AI agent teams to speed up a quantum error-correction decoder chip design

Canonical page: https://technooptimist.io/stories/ibm-uses-ai-agent-teams-to-speed-up-a-quantum-error-correction-decoder-48785fc6
Date: 13 Oct 2026
About: [IBM](https://technooptimist.io/companies/ibm.md)
Original source: https://research.ibm.com/blog/open-agent-factories-and-distributed-inference-for-chip-design

IBM Research used a team of AI agents to search for faster hardware designs for a quantum error-correction decoder. A coordinator agent directs parallel worker agents that propose alternative designs, and a verifier checks each one before designs are ranked by speed and hardware use. The work is a research study, not a finished product.

## Key facts

- The open-model configuration reached a 52x speedup over baseline for about $26 of inference cost, across 100 hypotheses.
- A proprietary frontier model reached a 204x speedup for about $299, about 11.5 times the open configuration's cost.
- The open configuration reached 60x at 200 hypotheses; doubling the search budget brought diminishing returns.
- The speedups are high-level synthesis estimates, and the costs cover model inference only, not synthesis or verification.
- The decoder tested is Relay-BP on a [[144,12,12]] bivariate bicycle code; llm-d, an open-source distributed inference framework, served the models.

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