Ninja Subnet Addresses LLM Inference Variance Issues

The team confirmed Minimax's model quantization changes caused score inconsistencies. They are transitioning to self-hosted GPU inference to stabilize evaluations and restarted validators with fresh king solves.

• •Validator restarted with freshly generated king solutions after Minimax backend changes degraded performance
• •Team committed to running local GPU inference to eliminate third-party provider variance
• •Challenger score anomalies traced to model quantization shifts, not code quality
• •Testing deepseek v4-flash as alternative inference model