Open source efficiency peaks with 1-bit models, abliteration

The early 2025 "efficiency revolution" marks a decisive pivot from brute-force compute scaling toward architectural and mathematical optimization. Native 1-bit models like BitNet b1.58 and Bonsai pruning are making SOTA reasoning viable on low-end consumer GPUs, while NVIDIA’s Nemotron-70B-Reward has established itself as the standard for preference alignment. Additionally, Pliny’s "abliteration" method ends the safety cat-and-mouse game by mathematically removing refusal vectors, and models like Qwen 2.5 and Gemma 2 are saturating the mid-range market with production-ready options.