| ▲ | consumer451 2 hours ago | |
super-edit: Sorry, this is not a usage related question, I have move it to: https://news.ycombinator.com/item?id=47772971 Here is the question for which I cannot find an answer, and cannot yet afford to answer myself: In Claude Code, I use Opus 4.6 1M, but stay under 250k via careful session management to avoid known NoLiMa [0] / context rot [1] crap. The question I keep wanting answered though: at ~165k tokens used, does Opus 1M actually deliver higher quality than Opus 200k? NoLiMa would indicate that with a ~165k request, Opus 200k would suck, and Opus 1M would be better (as a lower percentage of the context window was used)... but they are the same model. However, there are practical inference deployment differences that could change the whole paradigm, right? I am so confused. Anthropic says it's the same model [2]. But, Claude Code's own source treats them as distinct variants with separate routing [3]. Closest test I found [4] asserts they're identical below 200K but it never actually A/B tests, correct? Inside Claude Code it's probably not testable, right? According to this issue [5], the CLI is non-deterministic for identical inputs, and agent sessions branch on tool-use. Would need a clean API-level test. The API level test is what I really want to know for the Claude based features in my own apps. Is there a real benchmark for this? I have reached the limits of my understanding on this problem. If what I am trying to say makes any sense, any help would be greatly appreciated. If anyone could help me ask the question better, that would also be appreciated. [0] https://arxiv.org/abs/2502.05167 [1] https://research.trychroma.com/context-rot [2] https://claude.com/blog/1m-context-ga [3] https://github.com/anthropics/claude-code/issues/35545 [4] https://www.claudecodecamp.com/p/claude-code-1m-context-wind... | ||
| ▲ | onenite an hour ago | parent [-] | |
2 parent comments above say that you can use older version of claude code with opus 200k to compare. my guess is that eventually you’ll be able to set it in model settings yourself | ||