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I'd been on Codex for a while and with Codex 5.2 I: 1) No longer found the dumb zone 2) No longer feared compaction Switching to Opus for stupid political re

I'd been on Codex for a while and with Codex 5.2 I: 1) No longer found the dumb zone 2) No longer feared compaction Switching to Opus for stupid political reasons, I still have not had the dumb zone - but I'm back to disliking compaction events and so the smaller context window it has, has really hurt. I hope they copy OpenAI's compaction magic soon, but I am also very excited to try the longer context window.

iknowstuff 8mo ago
Hmm I’ve felt the dumb zone on codex
- nomel 8mo ago
  From what I've seen, it means whatever he's doing is very statistically significant.
mgambati 8mo ago
1m context in OpenAI and Gemini is just marketing. Opus is the only model to provide real usable bug context.
- hu3 8mo ago
  Source? I ask because I use 500k+ context on these on a daily basis. Big refactorings guided by automated tests eat context window for breakfast.
  - 8note 8mo ago
    i find gemini gets real real bad when you get far into the context - gets into loops, forgets how to call tools, etc
    - girvo 8mo ago
      I find gemini does that normally, personally. Noticeably worse in my usage than either Claude or Codex.
    - petesergeant 8mo ago
      I find Gemini to be real bad. Are you just using it for price reasons, or?
    - baq 8mo ago
      yeah gemini is dumb when you tell it to do stuff - but the things it finds (and critically confirms, including doing tool calls while validating hypotheses) in reviews absolutely destroy both gpt and opus. if you're a one-model shop you're losing out on quality of software you deliver, today. I predict we'll all have at least two harness+model subscriptions as a matter of course in 6-12 months since every model's jagged frontier is different at the margins, and the margins are very fractal.
  - Bolwin 8mo ago
    How many big refactorings are you doing? And why?
    - kimi 8mo ago
      How is that relevant? we are talking about models, now what you do with them.
- johnebgd 8mo ago
  Codex high reasoning has been a legitimately excellent tool for generating feedback on every plan Claude opus thinking has created for me.
- furyofantares 8mo ago
  I'm directly conveying my actual experience to you. I have tasks that fill up Opus context very quickly (at the 200k context) and which took MUCH longer to fill up Codex since 5.2 (which I think had 400k context at the time). This is direct comparison. I spent months subscribed to both of their $200/mo plans. I would try both and Opus always filled up fast while Codex continued working great. It's also direct experience that Codex continues working great post-compaction since 5.2. I don't know about Gemini but you're just wrong about Codex. And I say this as someone who hates reporting these facts because I'd like people to stop giving OpenAI money.
  - dotancohen 8mo ago
    [flagged]
    - deleted 8mo ago
      [deleted]
    - furyofantares 8mo ago
      When Anthropic said they wouldn't sell LLMs to the government for mass surveillance or autonomous killing machines, and got labeled a supply chain risk as a result, OpenAI told the public they have the same policy as Anthropic while inking a deal with the government that clearly means "actually we will sell you LLMs for mass surveillance or autonomous killing machines but only if you tell us it's legal". If you already knew all that I'm not interested in an argument, but if you didn't know any of that, you might be interested in looking it up. edit: Your post history has tons of posts on the topic so clearly I just responded to flambait, and regret giving my time and energy.
      - igor47 8mo ago
        I appreciate both your taking an ethical stance on openai, and the way you're engaging in this thread. The parent was probably flame bait as you say, but other people in the thread might be genuinely curious.
      - sho 8mo ago
karmasimida 8mo ago
This is true. When I am using codex, compaction isn’t something I fear, it feels like you save your gaming progress and move on. For Claude Code compaction feels disastrous, also much longer
pjerem 8mo ago
If you use OpenCode (open source Claude Code implementation), you can configure compaction yourself : https://opencode.ai/docs/en/config/#compaction https://opencode.ai/docs/en/config/#compaction
- comboy 8mo ago
  Not sure if it's a common knowledge but I've learned not that long ago that you can do "/compact your instructions here", if you just say what you are working on or what to keep explicitly it's much less painful. In general LLMs for some reason are really bad at designing prompts for themselves. I tested it heavily on some data where there was a clear optimization function and ability to evaluate the results, and I easily beat opus every time with my chaotic full of typos prompts vs its methodological ones when it is writing instructions for itself or for other LLMs.
  - brookst 8mo ago
    You can also put guidance for when to compact and with what instructions into Claude.md. The model itself can run /compact, and while I try to remember to use it manually, I find it useful to have “If I ask for a totally different task and the current context won’t be useful, run /compact with a short summary of the new focus”
  - copperx 8mo ago
    I ofter wonder if I'm missing something, but shouldn't we be able to edit the context manually??? In that way we could erase prompts and responses that didn't yield anything useful or derailed the model. Why can't we do that?
- genewitch 8mo ago
  so you have to garbage collect manually for the AI? also, i don't want to make a full parent post 1M tokens sounds real expensive if you're constantly at that threshold. There's codebases larger in LOC; i read somewhere that Carmack has "given to humanity" over 1 million lines of his code. Perhaps something to dwell on
- 8mo ago
radicality 8mo ago
Using Codex more for now, and there is definitely some compaction magic. I’m keeping the same conversation going and going for days, some at almost 1B tokens (per the codex cli counters), with seemingly no coherency loss

iknowstuff 8mo ago

Hmm I’ve felt the dumb zone on codex

nomel 8mo ago
From what I've seen, it means whatever he's doing is very statistically significant.

mgambati 8mo ago

1m context in OpenAI and Gemini is just marketing. Opus is the only model to provide real usable bug context.

hu3 8mo ago
Source? I ask because I use 500k+ context on these on a daily basis. Big refactorings guided by automated tests eat context window for breakfast.
- 8note 8mo ago
  i find gemini gets real real bad when you get far into the context - gets into loops, forgets how to call tools, etc
  - girvo 8mo ago
    I find gemini does that normally, personally. Noticeably worse in my usage than either Claude or Codex.
  - petesergeant 8mo ago
    I find Gemini to be real bad. Are you just using it for price reasons, or?
  - baq 8mo ago
    yeah gemini is dumb when you tell it to do stuff - but the things it finds (and critically confirms, including doing tool calls while validating hypotheses) in reviews absolutely destroy both gpt and opus. if you're a one-model shop you're losing out on quality of software you deliver, today. I predict we'll all have at least two harness+model subscriptions as a matter of course in 6-12 months since every model's jagged frontier is different at the margins, and the margins are very fractal.
- Bolwin 8mo ago
  How many big refactorings are you doing? And why?
  - kimi 8mo ago
    How is that relevant? we are talking about models, now what you do with them.
johnebgd 8mo ago
Codex high reasoning has been a legitimately excellent tool for generating feedback on every plan Claude opus thinking has created for me.
furyofantares 8mo ago
I'm directly conveying my actual experience to you. I have tasks that fill up Opus context very quickly (at the 200k context) and which took MUCH longer to fill up Codex since 5.2 (which I think had 400k context at the time). This is direct comparison. I spent months subscribed to both of their $200/mo plans. I would try both and Opus always filled up fast while Codex continued working great. It's also direct experience that Codex continues working great post-compaction since 5.2. I don't know about Gemini but you're just wrong about Codex. And I say this as someone who hates reporting these facts because I'd like people to stop giving OpenAI money.
- dotancohen 8mo ago
  [flagged]
  - deleted 8mo ago
    [deleted]
  - furyofantares 8mo ago
    When Anthropic said they wouldn't sell LLMs to the government for mass surveillance or autonomous killing machines, and got labeled a supply chain risk as a result, OpenAI told the public they have the same policy as Anthropic while inking a deal with the government that clearly means "actually we will sell you LLMs for mass surveillance or autonomous killing machines but only if you tell us it's legal". If you already knew all that I'm not interested in an argument, but if you didn't know any of that, you might be interested in looking it up. edit: Your post history has tons of posts on the topic so clearly I just responded to flambait, and regret giving my time and energy.
    - igor47 8mo ago
      I appreciate both your taking an ethical stance on openai, and the way you're engaging in this thread. The parent was probably flame bait as you say, but other people in the thread might be genuinely curious.
    - sho 8mo ago

karmasimida 8mo ago

This is true. When I am using codex, compaction isn’t something I fear, it feels like you save your gaming progress and move on. For Claude Code compaction feels disastrous, also much longer

pjerem 8mo ago

If you use OpenCode (open source Claude Code implementation), you can configure compaction yourself : https://opencode.ai/docs/en/config/#compaction https://opencode.ai/docs/en/config/#compaction

comboy 8mo ago
Not sure if it's a common knowledge but I've learned not that long ago that you can do "/compact your instructions here", if you just say what you are working on or what to keep explicitly it's much less painful. In general LLMs for some reason are really bad at designing prompts for themselves. I tested it heavily on some data where there was a clear optimization function and ability to evaluate the results, and I easily beat opus every time with my chaotic full of typos prompts vs its methodological ones when it is writing instructions for itself or for other LLMs.
- brookst 8mo ago
  You can also put guidance for when to compact and with what instructions into Claude.md. The model itself can run /compact, and while I try to remember to use it manually, I find it useful to have “If I ask for a totally different task and the current context won’t be useful, run /compact with a short summary of the new focus”
- copperx 8mo ago
  I ofter wonder if I'm missing something, but shouldn't we be able to edit the context manually??? In that way we could erase prompts and responses that didn't yield anything useful or derailed the model. Why can't we do that?
genewitch 8mo ago
so you have to garbage collect manually for the AI? also, i don't want to make a full parent post 1M tokens sounds real expensive if you're constantly at that threshold. There's codebases larger in LOC; i read somewhere that Carmack has "given to humanity" over 1 million lines of his code. Perhaps something to dwell on
8mo ago

radicality 8mo ago

Using Codex more for now, and there is definitely some compaction magic. I’m keeping the same conversation going and going for days, some at almost 1B tokens (per the codex cli counters), with seemingly no coherency loss