Introducing GPT-5.5 with Perplexity

By OpenAI

Categories: AI, Product

Summary

GPT-5.5 achieves 56% token efficiency gains over previous models, enabling developers to build internal tools in hours instead of days while maintaining performance on complex tasks. This dramatic reduction in computational overhead translates directly to faster user feedback loops and lower operational costs.

Key Takeaways

1. GPT-5.5 reduces token usage by 56% compared to previous models while maintaining performance quality on complex tasks, directly improving user feedback speed.
2. Token efficiency improvements enable rapid prototyping: developer built internal tool in under 1 hour using GPT-5.5 that previously would have required multiple days of development.
3. Optimizing workflows with GPT-5.5 creates measurable performance gains in production systems, not just in benchmarks—real-world agenda and computer workflows showed significant efficiency improvements.
4. Token efficiency directly impacts cost economics and user experience velocity; faster token processing reduces latency in feedback loops, improving end-user perceived performance.

Topics

• GPT-5.5 Token Efficiency
• LLM Cost Optimization
• Model Performance Benchmarking
• AI Tool Development Speed
• Workflow Automation with LLMs

Transcript Excerpt

GPT5.5 is very precise and very token efficient. One of the things I've I've been very impressed is I've been meaning to create this internal tool that quite some some time and I've been like always like deferring it because I thought like it's going to take me days, but then yeah, I took Codex and I put the new GPT5.5 into it and then yeah, I was able to do it probably under 1 hour. One of the big things we noticed was GPT5.5 is very efficient at [music] token usage. And not only internally we'...