3 ms·

Before GPT-5, I've used almost exclusively o3 and sometimes o3-pro. Now I'm using GPT 5 Thinking and sometimes GPT 5 Pro. So I think that I have some control ov

Before GPT-5, I've used almost exclusively o3 and sometimes o3-pro. Now I'm using GPT 5 Thinking and sometimes GPT 5 Pro. So I think that I have some control over quality. At least it thinks for few dozens of seconds every time.

energy123 1y ago
> GPT 5 Pro Have you noticed either of these things: (1) If your first prompt is too long (50k+ tokens) but just below the limit (like 80k tokens or whatever), it cannot see the right-side of your prompt. (2) By the second prompt, if the first prompt was long-ish, the context from the first prompt is no longer visible to the model.
- wrcwill 1y ago
  definitely 1! it seems to truncate your prompt even under the "maximum message length" and yeah around 55k is where it starts to happen. extremely annoying. o1 pro worked up until 115k or so. both o3 and gpt5 have the issue. (it happens on all models for me not just the pro variations) with the new 400k context length in api i would expect atleast 128k message lengths and maybe 200k context in chat.
  - energy123 1y ago
    Do you have a workaround? I'm putting the highest quality context into the 50k tokens, and attaching the rest for RAG. But maybe there is a better way.
    - wrcwill 1y ago
      i split the context and give it in two messages :/
- vbezhenar 1y ago
  Sorry, can't really answer to it, as I very rarely using any long context. I prefer to either edit previous question or just start new chat to keep context short. And even when I need to dump code, I prefer to choose relevant snippets. I'm aware that LLM quality degrades with long contexts, so I've trained myself to avoid it.