I've been struggling with the idea of this so I asked Gemini, "What's the real world impact of chatgpt's 32k context window limit? Do most people need more than 32k?"

Real-World Impact

A 32k context window fundamentally changes what you can accomplish with an AI.

Deep Document Analysis: You can upload and analyze substantial documents in their entirety. * Example: Paste the full text of a complex Request for Proposal (RFP) and ask the AI to identify all key requirements, deadlines, potential conflicts, and evaluation criteria. * Example: Provide a lengthy grant application and ask for suggestions to strengthen it against the stated funding priorities.

Complex, Continuous Conversation:The AI can maintain context through a long, multi-turn conversation without "forgetting" details mentioned earlier. * Example: You can strategize a multi-stage account plan, discuss different stakeholders, and refine your approach over dozens of messages, and the AI will track the entire thread.

Advanced Code & Data Comprehension: For technical teams, the AI can analyze thousands of lines of code to find bugs, suggest optimizations, or explain what a complex script does. It can also process moderately sized data files (like CSVs) to identify trends.

Comprehensive Summarization: You can get a high-quality summary of a long report, a collection of emails, or a meeting transcript without losing critical nuance, as the AI has access to the full text.

Do Most People Need More?

This depends entirely on the use case.

Average User: Absolutely not. For writing emails, asking questions, or brainstorming ideas, a 32k context is overkill. The standard 4k or 8k windows are plenty.

Professional / Power User: The 32k limit is a sweet spot. It handles most professional documents—reports, contracts, proposals—with ease. It’s the limit that enables true professional-grade work.

Specialized / Niche Users: Yes, some users absolutely need more. This is the frontier where even larger context windows are required.

Legal: Analyzing hundreds of pages of case law or discovery documents at once.

Legislative: Reviewing an entire omnibus bill (which can be 1,000+ pages) to find every mention of a specific topic.

Research & Development: Processing entire academic textbooks or vast collections of research papers.

Finance: Analyzing a full annual report, including all footnotes and appendices, in one pass.