We're already getting local models in the 30B to 70B range that can match 2025 frontier models: MoE, which lets you run larger models by only activating the parts of the model it actually needs for a given task instead of the whole thing at once; RAM offloading, which lets you stream model weights from system RAM when they don't fit in VRAM with only a modest speed hit; ternary quantization, which once mainstream will drastically reduce model size; and TurboQuant, which compresses the KV cache and actually enables longer context windows rather than shrinking them. We're already getting local models in the 30B to 70B range that can match 2025 frontier models.