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Nari Labs Achieves Sub-50ms Response Time for Text-to-Speech Model

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Nari Labs published a technical blog post detailing how they optimized a text-to-speech model based on Qwen3 to respond in under 50 milliseconds. The post outlines the engineering techniques and architectural decisions used to push the model to the speed-cost frontier. The work focuses on reducing latency while managing computational costs for real-time speech synthesis. The article was shared on Hacker News, where it attracted early community attention.

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Nari Labs Achieves Sub-50ms Response Time for Text-to-Speech Model · ShortSingh