# RunPod GPU Scanner ## Purpose Query RunPod API to show available SECURE cloud GPUs in the EUR-IS region with ≥16GB VRAM. ## Requirements - Python 3.7+ - python-dotenv (`pip3 install python-dotenv`) - requests (`pip3 install requests`) - Valid RunPod API key in `/home/jgrusewski/Work/foxhunt/.env.runpod` ## Usage ### Run the script: ```bash # From foxhunt root directory ./scripts/scan_gpus.py # Or with python3 python3 scripts/scan_gpus.py ``` ## Output The script displays: - GPU name (e.g., RTX 4090, A100 SXM) - VRAM capacity (GB) - Price per hour (USD) - Availability (number of pods) Results are sorted by price (cheapest first). ## Filtering Criteria - Memory ≥16GB VRAM - Secure Cloud availability > 0 - Valid pricing information - EUR-IS region ## Example Output ``` ====================================================================== RUNPOD SECURE CLOUD GPUs (≥16GB VRAM) - EUR-IS REGION ====================================================================== GPU Name VRAM Price/hr Available ---------------------------------------------------------------------- RTX A5000 24GB $0.160 True pods RTX A4000 16GB $0.170 True pods RTX 4090 24GB $0.340 True pods ... ====================================================================== Total GPUs found: 24 ``` ## Top Recommendations for Foxhunt ML Training Based on the current scan results (October 2025): ### Budget Option (FP32 Models) - **RTX 4090**: $0.34/hr, 24GB VRAM - Best value for FP32 training (TFT-FP32 fits in ~500MB) - Ideal for initial deployment and baseline metrics ### Professional Option (QAT Models) - **RTX A6000**: $0.33/hr, 48GB VRAM - Best for QAT training (requires gradient checkpointing) - Can run multiple models concurrently ### Enterprise Option (Multi-Model Inference) - **A100 PCIe/SXM**: $1.19-1.39/hr, 80GB VRAM - Production-grade for ensemble inference - Supports 4+ models with headroom ## Notes - Prices and availability fluctuate based on demand - Run this script regularly to find the best deals - Consider spot instances for training (not shown in this script)