DeepSeek V3.2
-
Deepseek v3.2 on 16 AMD MI50 GPUs: Efficient AI Setup
Read Full Article: Deepseek v3.2 on 16 AMD MI50 GPUs: Efficient AI Setup
Deepseek v3.2 has been optimized to run on a setup of 16 AMD MI50 32GB GPUs, achieving a token generation speed of 10 tokens per second and prompt processing speed of 2000 tokens per second. This configuration is designed to be cost-effective, with a power draw of 550W when idle and 2400W at peak inference, offering a viable alternative to expensive CPU hardware as RAM prices increase. The setup aims to facilitate the development of local artificial general intelligence (AGI) without incurring costs exceeding $300,000. The open-source community has been instrumental in this endeavor, and future plans include expanding the setup to 32 GPUs for enhanced performance. Why this matters: This development provides a more affordable and efficient approach to running advanced AI models, potentially democratizing access to powerful computational resources.
-
AI Models Tested: Building Tetris
Read Full Article: AI Models Tested: Building Tetris
In a practical test to evaluate AI models' capabilities in building a Tetris game, Claude Opus 4.5 from Anthropic delivered a smooth, playable game on the first attempt, showcasing its efficiency and user-friendly experience. GPT-5.2 Pro from OpenAI, despite its high cost and extended reasoning capabilities, produced a bug-ridden game initially, requiring additional prompts to fix issues, yet still offering a less satisfying user experience. DeepSeek V3.2, while the most cost-effective option, failed to deliver a playable game on the first try but remains a viable choice for developers on a budget willing to invest time in debugging. This comparison highlights Opus 4.5 as the most reliable for day-to-day coding tasks, while DeepSeek offers budget-friendly solutions with some effort, and GPT-5.2 Pro is better suited for complex reasoning tasks rather than simple coding projects. This matters because it helps developers choose the right AI model for their needs, balancing cost, efficiency, and user experience.