Скачать или смотреть 1,000 Tokens Per Second: The GPT-5.3 Secret

OpenAI just dropped a model that writes code faster than you can read it. 1,000 tokens per second is finally a reality, but the real story is the massive hardware shift making it possible. In this video, we deep dive into the 'Great February Model Rush' and the release of GPT-5.3-Codex-Spark.

We explore why OpenAI is moving away from NVIDIA GPUs for this specific model and how Cerebras Systems' wafer-scale hardware allows for near-instantaneous software generation. This isn't just a minor update—it's the death of the loading bar for developers and a fundamental shift in how we interact with AI engines.

What you will learn:
How Cerebras chips differ from traditional GPUs for AI inference
The engineering behind GPT-5.3-Codex-Spark’s record-breaking speed
Why OpenAI retired the 'human-like' GPT-4o in favor of high-speed performance
The real-world impact of zero-latency AI on software engineering and iteration

Chapters:
00:00 The 1,000 Token-per-Second Milestone
02:15 The Hardware Shift: Cerebras vs. NVIDIA
04:30 GPT-5.3-Codex-Spark Architecture Explained
06:45 Why 'Personality' is Being Replaced by Speed
08:30 Building at the Speed of Thought
10:00 What’s Next for Low-Latency AI

If you find these deep dives helpful, make sure to like the video and subscribe for more technical AI analysis. Let us know in the comments: would you trade AI personality for 10x more speed?

#OpenAI #GPT5 #AIHardware #Cerebras #SoftwareEngineering