AMD Radeon AI Pro 9700 Dual-GPU Local AI Setup: Updated Models and Inference Engines (October 2026)

An updated look at running local AI models on a dual AMD Radeon AI Pro 9700 setup, covering the latest recommended models, inference engines, and performance configurations as of October 2026. The video benchmarks multiple engines tailored to specific GPU architectures and model formats, comparing token generation and prompt processing speeds across single and dual GPU configurations.

■ Recommended Models & Inference Engines
- Qwen 3.8 27B and Flash Next model families
- GGZ14 engine with speculative decoding (D Flash 2)
- R9V, Rob's VLM build, and Radiance engines
- llama.cpp with ROCm/Vulkan backends as baseline

■ Benchmark Methodology & Results
- OpenAI-compatible endpoint testing simulating agent workloads
- Single-GPU vs. dual-GPU comparisons at 32K–64K context depths
- Prompt processing and token generation speed measurements
- Multi-request concurrency testing

■ Setup & Configuration
- Server build overview (Ryzen 9 9900X3D, 64GB RAM)
- AI Toolbox Cockpit for engine installation and parameter tuning
- Quantization formats: MX FP4, FP8, dynamic quantization

Ideal for users running or considering a local AI workstation. Viewers will gain a practical understanding of which model and engine combinations deliver the best results on AMD Radeon AI Pro hardware, and how to configure them via AI Toolbox Cockpit.