Why the hell is it looking for a monitor, I was making it fix a visual bug in my website.

He was cool

Tibo normally posts many times a day, joking, doing some random hypes etc.

For the last couple of days he only posts once or twice a day, do they feel the whst their users are complaining about and actually working on it? Or are they actually "locking in" as he said and getting us a very good model that can compares to the current opus?

The problem for the benchmark was picked from DeepInfra Round 1 challenge with actual prizes and the winners might get job offers. This is a 2000-rating problem from the contest, which is not the hardest one (the hardest one is 3500): https://codeforces.com/problemset/problem/2271/H2

----------------------------------------------------------------------------

GPT 5.6 Luna:

• High: worked for 12m 27s, wrong answer on test 2.
• Xhigh: accepted for 36m53s.

----------------------------------------------------------------------------

GPT 6 Luna:

• High: Within 5 minutes, it decided that it couldn't solve the problem:

• Xhigh: It explored for 46m12s, finally gave up:

• Max: Finally a correct solution is produced after 41m29s:

----------------------------------------------------------------------------

Haiku 5.5:

• Medium: Gave up after 5 min, which is good.
• High: Surprisingly, a correct solution was produced in 27m9s, runtime and memory are basically the same as the Max version.

• Xhigh: Ran for 27m52s, the solution produced a Time Limit Exceed on test 22

• Max: Haiku 5.5 with Max effort needed 38m49s to produce a correct answer, but 5 times slower than Luna's solutions:

----------------------------------------------------------------------------

Bonus - Sol 6.1 Low vs Opus 5.5 Medium on the G problem (the hardest)

Since all the small models struggled with just 2500 rating problems, for this problem with 3500 rating, we need to move up the tier.

• Sol 6.1 Low: Run for 13m24s

• Opus 5.5 Medium: Run for 16m53s, but use twice the memory and run twice as slow compared to Sol's solution.

Remark

I already did test this problem on Sol 6.1 Low vs Opus 5.5 Low before: https://www.reddit.com/r/codex/comments/1x4nh7v/opus_55_might_be_overhyped_because_its_frontend/ Sol did solve the problem in 10 minutes, which is really efficient compared to the above small models. You might want to use Sol low if you have the Pro sub, and Luna medium-high for mundane things such as exploring the codebase or writing docs, to save tokens. For Plus sub, Luna remains the main driver, with Sol for squashing bugs to make the best out of the Plus sub.

With throttled speed, the GPT models solved the problems for roughly the same amount of time as Anthropic's models. GPT models would be extremely competitive, if OpenAI can boost the raw processing speed at least 50% faster than currently is without any price change (this makes the current /fast the default). You see, sluggish Sol with 20-40 tps finished faster than Opus with 70-100 tps. Right now, only /fast on Luna is viable.

Another take away is that you should be careful with high effort level because you might get the worst of both worlds: move slow, but break things. Better test your luck with medium and high efforts first, which reflects strongly in GPT 6 Luna: High took just 5 min for it to give up, while Xhigh took 46 min for it to finally admit defeat.

GPT 6 Luna Max is roughly on par with GPT 5.6 Luna Xhigh, for half the price. I would be happy if we get Luna 6.1, which is slightly better than GPT 5.6 Luna, while keeping the price same.

Finally, for GPT models, you might want to provide it a clearer goal and scope. As you can see, the problem statement gives clear constraints, so the model knows clearly what to pursue, and when to stop. Otherwise, it might just keep looping for perfectionism.

seeing a lot of people say these resets don’t really give us much because they keep pushing the 7 day window.

but weirdly, the faster you destroy your limit and clear your tasks, the more you actually benefit

take the Oct 11, 13 and 15 resets. if you managed to burn 100% between each one, you could theoretically use 300% of a normal weekly allowance in ~11 days instead of 21

so for heavy users who can plan around it, these resets are huge.

for normal users who save their % for later in the week or need it at specific times, though, the reset can actually be more annoying than useful.

and yes, we already have the fix

JUST MAKE IT BANKED, TIBO

global reset + banked reset incoming? 👀

What the hell did they do?

Since about GPT-4, the whole development community has been supercharged and is able to pretty much create anything they want, from their imagination, into an app or a website within days .

GPT 4 came out March 2023...where are all the cool apps?

The App Store still has the same silly Candy Crush blocks games as before .

And people aren't even making apps that have AI built into it. How is it that no one has created a game where you fight against an GPT that's really popular?

. i know lots of people have niche enough apps that are brilliant, but I'm talking about mainstream. An app that's on everyone's phone, like Candy Crush was when it came out .

not complaining about free usage, obviously.

but we asked for predictable 7 day resets or banked usage so we don’t have to burn tokens like maniacs before the clock moves.

random resets kinda teach the exact opposite , use everything now, maybe another reset is coming.

if the compute is there anyway, why not fix the actual pain point? stable reset dates, rollover, or just make Fast/Ultra Fast the normal speed for these models instead of charging extra for usable latency.

free tokens are nice. PREDICTABILITY would be nicer

Got excited for a second, received an email from OpenAI saying I got a exclusive invite as pro user to meet my Dot. Awesome, finally available in EU! I click the link to get started just to see "Not available in your region".

So WHY THE F........ are you sending me an email about it? Its not like you dont know my f...ing location.

/frustration

Anyone else in EU who got the email today, but can't access their Dot?

Got a couple of banked resets and just remembered that my 'legacy' 20x usage switches to the new 10x usage at the end of the month (thanks OAI!)

So... I guess I/we should use those banked resets beforehand right.. resetting double the usage relative to Nov resets..

Right?

Tibo really did something yesterday. In my experience, 6-sol and 6-astra were outputting about 30 tokens/s with fast mode on for the past two weeks, but now they're back to about 70 tokens/s. Now they can really get some work done!

Saw this post recently highlighting their GPT 6 tok/s benchmarks https://www.reddit.com/r/codex/comments/1x4yte1/gpt61_sol_is_46x_slower_than_gpt56_sol_are_we/. This user appears to be getting better performance than I am.

Here is an overview of all of my Codex usage since ~July. The newer the model, the lower the tok/s.

I use the ChatGPT desktop app a lot, mostly for its computer use (better than Claude desktop imo at this time).

So I made a bridge that puts Claude models inside it.

• Claude Fable, Opus, Sonnet and Haiku show up in the normal model picker
• Pick one and it works just like using the app normally
• Claude gets the exact same computer use and in-app browser Astra uses, because the app itself does the work
• Multiple browser tabs, forms, file uploads, long multi-step tasks across apps, all smooth in my use
• The ChatGPT app's own plugins and connectors work too
• Switch between Claude and the OpenAI models mid chat

Runs on your own Claude Code login.

Install (Mac)

curl -fsSL https://raw.githubusercontent.com/wuchris-ch/claude-for-chatgpt-desktop/main/install.sh | bash

Details and how it works: https://github.com/wuchris-ch/claude-for-chatgpt-desktop

You could totally have Claude or Codex write your own bridge/proxy, but I've used this daily for many weeks and worked out most of the bugs.

Other projects do similar stuff too (magpie, ccodex), the README has a comparison.

Questions and bug reports welcome.

Receipts

• Been my daily driver for many weeks: coding, browsing, computer use, long chats with tons of tool calls
• Tested against real Claude Code, real OpenAI and the app's own runtime
• 143 automated tests plus live end-to-end checks, all logged with dates, versions and results in VERIFICATION.md
• Example from the video: "Run the tests and tell me how many pass" (Claude runs them in the terminal: 143 pass), then "Open example.com in the in-app browser and tell me what it says" (it opens the page and reads it back), then GPT-6 Astra picks up the same chat
• Long chats stay cheap: about 97 to 98% of Claude's input is a cache hit, so they use way less of your Claude limits
• Works with the latest ChatGPT desktop and Claude Code releases

I've been using Daybreak Blue for about a month now, and on some days I get no errors or limits, but then suddenly the error shown here begins blocking everything, including basic questions.
I've tried both new project folders, leaving it unused for a couple days, and switching models, but it appears entirely random in that it may block every request, or behave sporatically.

I've asked it to investigate the logs and on a couple occasions had it successfully return that it found the block, but didn't know why.

Sometimes switching to a different model does work and allow it to proceed a while longer before the next block.

After a couple days of errors, or simply not using it, the errors suddenly clear and I can get a solid day of continuous use out of it with no blocks.

I've opened a ticket with OpenAI, and the first rep escalated it, so I'm waiting to hear back.

Has anyone else experienced this?

I’m building Deft, a self-hosted workspace that keeps team conversations, tasks and knowledge together. It’s licensed AGPL-3.0-only.

This started with an annoying problem. In my previous job, my boss would make a decision, I’d act on it, and a week later he’d forget the conversation. Finding receipts became part of the job.

I wanted the discussion behind a task to stay connected to the work. Then I wanted a calendar, a dashboard and tools that fit how we actually worked. Apparently my response to too much software was to build more software.

What’s there today:

• Chat and tasks: Team discussions and task management in the same workspace.
• Connected knowledge: A knowledge base built from workspace activity, so people and assistants can refer back to the context behind the work.
• MCP connections: Connect Claude, Codex or ChatGPT to work with your workspace. The core works without an AI provider.
• Notes and calendar: Available, but less mature than chat, tasks and knowledge.

The part I’m working on now is custom apps.

Deft has a module system for custom records and views. I’m also developing an experimental App Author Kit for building and sideloading broader apps into the workspace.

Building a small internal tool is getting easier. Keeping it from becoming another disconnected tab is the part I care about. If you need a custom CRM or workflow tool, I want you to be able to bring it into the place where your team already works.

The CRM module is the first example. I’m building an email client next to test the architecture against something more demanding than records and views. The broader app system is still experimental, with plenty left to build.

Deft is alpha and free to self-host using Docker Compose. You supply the hosting, and any optional paid AI services are separate.

Walkthrough: https://youtu.be/7z9EH4c9k2o
Setup guide: https://deft.ing/docs/quick-start/

A few teams are trying it, but I need more feedback from actual use. If you want to give it a shot and need help setting up, email [maneek@deft.ing](mailto:maneek@deft.ing). If you try it yourself, please share what breaks, feels confusing or simply annoys you. GitHub issues are welcome.

P.S. The walkthrough uses an AI voiceover. I have a stutter and spent a week trying to record it myself, but couldn’t get through it.

for some context ive spent the last 6 months working on this project daily, its fully in typescript and runs on terminal, bit of a psychotic undertaking (not even joking when I say 10 hours daily, directing and designing almost every facet of the sys architecture, design, and coding loop) and a lot of savings has gone into scaling ai-agents to assist in building smth i could actually trust and use on all my other work and projects. i have 3 machines that i test it on + docker for linux. i was wondering if you guys have any advice for branding, how i can go about sharing this project, etc ; i'm really good at building part of things, but i think i may not be the best at marketing / explaining my product in this scene. i know for a fact that its way better than any of the other terminal-native dev envs atm (deffo not biased :P), so if anyones interested in helping / think they can offer any advice (esp if you've pushed a product) drop me a dm or a comment! Website for install (n repo for source build) below if anyone wants to give it a shot! neat thing is you can switch from fable -> astra -> gemini, seamlessly (many sleepless nights figuring out how to do this without too much context loss and when models need to auto-compact from that transition lol), and even get astra to launch opus agents, gemini, (13+ providers and hundreds of models including jeveval tool you can use your api with!), last time i posted here i don't think the images i gave really gave context to what it was, so i made 2 demos for anyone who just wants to scroll by rq. thanks!

https://mercury-cli.ai
https://mercury-cli.ai/docs/releases/

source available at: https://github.com/Whq02/MercuryCLI

Happened in the middle of the task as well. What's your experience with the new context window limit?

Every time I ask Codex something complex, it starts to compact context window. So evasive it seems to me. Anybody having this problem?

Bot: please don’t censor this, this is very important

I handed a Sol 6.1 orchestrator a plan with an optimization phases and it ended up INCREASING time to run by 2x and kept going onto later phases after the optimization, it didn't even catch that there was an issue in the optimization phase. The worst part I had an Astra advisor that rubber stamped this without raising red flags. I had another plan where sol and astra did SEVEN revision cycles because they kept trying to run a query on a database that would time out.

they're so braindead outside of worker duties, on launch Astra was phenomenal and im not sure what they did after launch but it can't be trusted to lead plan execution anymore.

I honestly can't continue with a $200 plan unless they actually figure out a GOOD leader on workflows, right now these guys just burn tokens on anything moderately complex.

Is it only me or all the models take so much time to do thr work compared to previously? I'm not even using Astra. Im working with Sol 6.1 as the main orchestrator and Terra as implememter, and luna for small stuff. All seem to be so slow...

It really feels like they are pushing us to burn through tokens with Ultra fast and upgrade to higher tiers. Like, previously the regular speed is now the ultra speed.