HN user
DeepSeek’s docs say V4 has a 1M context length. Is that actually usable in practice, or just the model/API limit?
Codex shows ~258k for me and Claude Code often shows ~200k, so I’m curious how DeepSeek is exposing such a large window.
Great, thanks for clarifying :)
Congrats on the release! Is Images 2.0 rolling out inside ChatGPT as well, or is some of the functionality still going to be API/Playground-only for a while?
I like the "between artifacts" framing. One layer I'd add is proxies/metrics. In a lot of analytics-heavy systems, the real loss isn't spec -> code, it's question -> proxy. Once the proxy gets baked into acceptance criteria, dashboards, or evals, people optimize that and gradually forget it was only a proxy.
this post needs an enema
OpenAI has been doing the same thing gradually. Codex launched with generous Plus limits, then they introduced the $100 Pro tier, and Plus limits have quietly tightened since. With the same repetitive tasks I was running, consumption is noticeably higher now for the same output.
The pattern feels deliberate — make the $20 tier just uncomfortable enough that power users upgrade, without officially announcing the reduction. If it continues, $20 buys you a demo and $100 buys you actual work.