Researchers introduce TelecomGPT-R1, a family of open-source unified telecom reasoning models designed to automate engineering tasks by reasoning over standards, configurations, and logs. The model addresses the limitations of existing general-purpose and specialized LLMs through a structured approach covering protocol, knowledge, modeling, and fault axes.

  • An axis-aware data generation framework refines public telecom artifacts into 104,880 verified question-answer pairs with chain-of-thought reasoning.
  • Supervised fine-tuning instills telecom knowledge to overcome the cold start barrier for reinforcement learning.
  • Dynamic sampling policy optimization (DAPO) with task-routed rubric rewards stabilizes RL updates across heterogeneous tasks.
  • The TelecomGPT-R1-27B model achieves an 89.64% mean score on seven GSMA Open Telco Leaderboard benchmarks, outperforming GPT-5, Claude, and Gemini.

The authors release the models and a reproducible training recipe to support community development in telecom automation.