LocalLLaMA user weighs AMD R9700 VRAM upgrade

The 32GB VRAM on the R9700 is essential for running models like Qwen3.5 35B with full context windows without resorting to extreme offloading or speed-killing quantization. Local agent frameworks like OpenClaw rely on consistent, low-latency token generation which is only possible when the KV cache and model fit entirely in video memory. AMD's AI PRO lineup offers a cost-effective alternative to enterprise NVIDIA hardware, finally matching raw VRAM capacity at a lower entry price for workstations. While software optimizations like TurboQuant offer temporary relief for 16GB cards, they cannot match the physical reliability of a larger frame buffer for 100k+ token sessions. This hardware shift marks the evolution of local LLMs from simple chat interfaces to persistent, context-aware development assistants.