South Korea · Models & research

Meta AI's 8B Model Ties Claude Opus 4.5 on Agent Benchmark With EvoHarness-RL

Researchers from Meta AI and the University of Illinois Urbana-Champaign trained an 8-billion-parameter open model, Qwen3-8B, using a new reinforcement-learning method called EvoHarness-RL. On the ALFWorld benchmark for multi-step agent tasks, it reached a 96.9% success rate — edging out Claude Opus 4.5's 96.4% and up 49 points from the untrained baseline.