New Delhi, Feb. 13 -- When OpenAI introduced GPT-5.3-Codex-Spark, the headline takeaway was obvious: real-time coding, near-instant responses, and more than 1,000 tokens per second. But beneath the performance metrics sits a more consequential signal for enterprise AI adoption: latency is becoming a strategic differentiator, not a technical optimisation.

Codex-Spark is not positioned as a replacement for large frontier models. Instead, it reframes how developers interact with AI systems in production environments, where waiting, even seconds, can break workflow momentum.

Until now, most progress in coding models has focused on reasoning depth: longer context windows, autonomous execution, and multi-step task completion. Codex-Spark take...