Key Takeaways Compression breakthroughs are collapsing the hardware barrier. TurboQuant achieves 6x memory reduction with zero quality loss, and PrismML's 1-bit Bonsai 8B fits a competitive model in 1.15 GB — 14x smaller than its 16-bit equivalent. Models that required data center GPUs now run on a MacBook Pro or even a phone. Edge AI is earning a permanent place in the coding agent stack, not replacing the cloud. The open-source capability gap has closed to roughly three months. Gemma 4 ships edge-first with native function-calling under Apache 2.0, and Reflection AI's $2.5B raise signals that enterprises and infrastructure providers are investing in locally-deployable coding models as a complement to cloud services. Reinforcement learning is making tiny models genuinely useful for agent orchestration. LiquidAI's 350M-parameter model — 1/20th the size of GPT-2 — achieves over 95% accuracy in multi-turn tool-calling, running on hardware as small as a Raspberry Pi.…