DEEPSEEK RELEASES FREE OPEN SOURCE TOOL THAT MAKES AI MODELS RESPOND 85 PERCENT FASTER DeepSeek just dropped another open source project and the numbers are hard to ignore. DSpark is a new inference optimization framework released under the MIT license, meaning anyone can download, use, and modify it at no cost. According to DeepSeek, the system can reduce LLM response latency by up to 85 percent without changing what the underlying model is actually computing or producing. The core innovation sits in how requests are batched, scheduled, and processed at the hardware level. By rethinking the serving pipeline, DSpark extracts substantially more throughput from existing GPU infrastructure without requiring companies to purchase additional compute. That last part carries real weight in a market where GPU capacity is expensive and heavily backlogged. For companies running large-scale inference operations, shaving 85 percent off response time while maintaining full model quality translates directly to lower infrastructure bills and faster products. DeepSeek has now established a consistent playbook. Release powerful models and tools at low or zero cost, usually open source, and let market adoption do the work. This strategy has repeatedly undercut American AI labs on price and accessibility. DSpark arrives as US companies face mounting pressure to cut AI spend. It gives engineers a concrete, free tool to do exactly that. Keywords: DeepSeek DSpark, LLM inference speed, open source AI, AI efficiency 2026, DeepSeek open source