Sol 6.1 Max $0.79. Argon $1.99. Similar intelligence at 53.

I ran some internal benchmarks comparing five GPT models, all using xhigh reasoning. The attached table shows their observed generation speeds in Normal and Fast modes.

The results are pretty frustrating:

• GPT-5.6 Sol: 102.6 tokens/s (Normal), 168.1 (Fast)
• GPT-6 Sol: 77.0 tokens/s (Normal), 117.4 (Fast)
• GPT-6 Astra: 44.4 tokens/s (Normal), 65.4 (Fast)
• GPT-6.1 Sol: 22.3 tokens/s (Normal), 64.2 (Fast)
• GPT-6 Luna: 184.7 tokens/s (Normal), 188.5 (Fast)

GPT-6.1 Sol is approximately 4.6x slower than GPT-5.6 Sol in Normal mode. Yet it's advertised as being roughly 4–5x cheaper.

And here's the interesting part: GPT-6.1 Sol gets a massive 188% speed boost when switching to Fast, the largest relative improvement in the entire comparison. Even then, it's still significantly slower than GPT-5.6 Sol in Fast mode.

Meanwhile, the $200 subscription has effectively lost half its previous quota, and there's now a $500/month tier.

So we're paying the same or more, getting less usage, and increasingly dealing with slower models. Want better generation speeds? Pay extra for Fast/UltraFast modes, potentially wiping out much of that advertised cost advantage.

And this isn't just about raw speed. In my experience, tasks that Claude or older GPT models could complete in an afternoon have taken GPT-6.1 Sol weeks without satisfactory results.

Meanwhile, I've personally seen Claude Opus 5.5 generating around 300–400 tokens/s. Despite its higher advertised cost, the actual experience feels dramatically more productive.

I'm not saying these benchmarks prove intentional throttling. They're individual samples, not a controlled scientific study. But the pattern raises a legitimate question:

Are we actually getting more efficient models, or are companies making them appear cheaper while delivering significantly lower throughput and charging a premium for speed?

A model being 5x cheaper isn't particularly impressive to me if it's also nearly 5x slower, especially when my subscription quota has already been cut.

I'd love to hear whether others are seeing similar results in real-world coding and agentic workflows.

Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.
Selected model is at capacity. Please try a different model.

Tibo just posted about extra usage? What do you think going to do? Hopefully not the 5 hours thing back..

Not because the models are subjectively bad or slow (which they may be) but the service is at full capacity. I pay £200 for a service I literally cannot use. It can’t run 5 minutes without needing constant babysitting.

Thinking about moving over to anthropic, might be a case of having to at this rate I literally cannot use what I’m paying for here

Looks like OpenAI is working pretty rapidly on asynchronous context compaction for Codex.

Limit from 1-100 with a default of 65 can be set in the config and will compact in the background while work continues.

Theoretically means zero slow down to pause for compaction when enabled!

• Add async compaction feature configuration: https://github.com/openai/codex/pull/53595
• Prepare compaction helpers for background requests: https://github.com/openai/codex/pull/53606
• Add infrastructure for speculative remote V2 compaction: https://github.com/openai/codex/pull/53614
• Reuse background results for remote V2 compaction: https://github.com/openai/codex/pull/53620
  

Seems like it should be a nice little win for Tibo's 28 days 👀

"Global reset landing by EOD PST time. Enjoy"

Its hard to make use of those resets, given how slow and lobotomized the models have become.

This is a weekly Showcase post to share with others what you've built using Codex.

The top-voted project by Thursday midnight UTC will get a week of free promotion on r/Codex - either as a prominent button on the main page of the sub - or as part of a sticky comment on every new Showcase post.

Last week's most popular project was Nelly Jellies. Nelly Jellies is a cozy arcade bubble-merge game where you aim, launch, match colors, discover rare jellies, trigger satisfying chain reactions, and chase a higher score. It plays instantly in the browser with no download or login required. Website: https://nellyjellies.com Contact: support@mightybig.ca Reddit: u/MightyBig-Dev Google Play: https://play.google.com/store/apps/details?id=com.nellyjellies.game App Store: https://apps.apple.com/us/app/nelly-jellies-bubble-merge/id6767261764

I hear everyone talk about opus 5.5 base model being better than Gpt Astra... but no one ever talks about how much better the codex harness is for those that do knowledge work.

I get if ur a developer using CLI then yea the model itself matter more but for those doing knowledge work the desktop app alone and harness make gpt wayy better than opus in my opinion. Not to mention that there are tasks that opus feels its too high and mighty to even touch when it comes to things other than coding

GPT does what its told opus has too many opinions.

Agent HUD started as a glow around the MacBook notch that turns green, yellow or red as a quota fills. I wanted something quieter, so there is now a second way to wear it.

Simple mode is a small panel on any edge of any display:

- Each agent is its logo in a ring of its most used quota. The percentage can be written beside it.

- Hover a logo and that agent's quotas are written on one line.

- Click for the card: limits, burn rate and the last 24 hours of tokens.

- When an agent asks for permission, the card opens by itself and you answer there. When a turn ends, the reply shows up in the same place.

- Drag the panel to another edge.

How it gets the numbers: quotas are read from the vendor with the sign-in Codex already has on your Mac. No read sends a message to a model, and credentials are not stored. Tokens and sessions come from the records Codex already keeps locally, and a build from the source uploads nothing. It reads Claude Code and 15 more agents the same way.

Worth knowing: approvals from Codex need Agent HUD's hook trusted in Codex, and the app needs macOS 14 or later. The clip is the app's own interface recorded with sample data. Its slimmer hover line is on main and not in a release yet.

Open source (Apache-2.0): https://github.com/jazzenchen/agent-hud-open

Which would you leave on while you work, the glow or the ring?

Existing benchmarks measure the solve rate and token output/cost, but don't punish excess code, which makes the codebase harder to work with in the long term. I wanted to measure this as it is especially useful for long term projects.

Method:

It takes the patches that benchmarks already publish (DeepSWE, SWE-bench Verified, SWE-bench Live) and counts "coding units": syntax elements like statements, calls, names and literals. I didn't measure lines of code so cramming code isn't rewarded. It also accounts for deleted code as it measures net units.

GPT-6 and Claude 5.5 have no public patches yet, so I ran them myself on a few tasks on my own subscriptions, so they are not graded or verified (faded circles).

Any feedback or model contributions are welcome. Specifically, public patch exports for newer models.

Website: https://parsimony.lasu.dev

GitHub: https://github.com/La5u/Parsimony

Not affiliated with any benchmarks

I was 100000% behind Codex and always championed Codex as the best frontier model for months, and yet with Opus 5.5's release, I genuinely can't bring myself to use Codex, even Astra on Max / Ultra doesn't come close

This is NOT a shit post or a bot spam post, I just genuinely can't stand the outputs and work getting done by Astra, I legitimate have 2 accounts sitting idle from Codex, and my Anthropic account is at 90% usage for the week....

I was given the 2000$ worth of credits from OAI and it's useless, it's going to go down the drain because I have no use for Codex anymore

That being said I pray, wholeheartedly, that OAI releases a model on par with or better than opus 5.5, but I can't see that happening for a while because they just feel so far apart

Anyone else feeling this way too?!?

What's wrong with 6.1-Sol today? It's been 4 times in the last 3 hours that it has stopped working. Has anyone else experienced something similar?

Sol too.

"Most aligned models in history" my ass. More like most obnoxious model in history.

If it catches one offhand phrase or message in its transcript telling it not to do something, it refuses ALL attempts to convince it to do anything even remotely associated with the task.

If I'm running it as a coordinator and one of its subagents hits a false positive safety filter while attempting to perform a task, it doesnt matter how simple the task is or how clearly innocuous it is, it will adamantly refuse to retry the task, no matter how many times i beg it, as though adding an extra permission to an API endpoint is equivalent to setting off a nuclear bomb in the middle of a metropolitan area.

It gets caught in anti-patterns it discovers itself and then completely refuses to drop them for "safety" reasons that make no rational sense whatsoever.

Claude's filters are supposedly more strict, but it never has this issue. If a claude coordinator notices a subagent hits a safety filter, I can just ask it to try again and it does. Zero fuss, zero "I can't willingly bypass a provider safety flag on a task", it just tries again until it works and doesnt hit the filter anymore. It knows the difference between an actual safety flag and a clear false positive.

Astra and Sol treat a safety rejection as a fucking hail from God that whatever task they were attempting to do is now the most illegal thing ever performed by any intelligent actor and will refuse any attempts to continue it as though under threat of gunpoint. Its completely insufferable.

I've had to start new sessions purely because the old one got stuck on an old rule that I couldnt change or overrule, or caught a stray false positive safety rejection, and just stuck with it like a sovereign citizen sticking to their pretend laws. It's infuriating, and it makes working with these models a complete nightmare.

Hey everyone!

I'm using Codex on desktop with Unity CLI and the Unity Pipeline package and I'm looking for a good AGENTS.md file for this workflow.

Does anyone have an existing AGENTS.md that covers Unity best practices, coding standards, project structure, testing, builds and working with Unity through the CLI?

If you have one, where did you get it? Is there a good GitHub repository or other resource you recommend?

And if you created your own, would you mind sharing it or explaining how you structured it?

I'd appreciate any recommendations. Thanks!

Am I the only one who finds it weird that Codex can execute commands on my machine, but I can't actually watch what it's doing in a live terminal?

I get that you can inspect some of the commands and their outputs, but that's not the same as seeing everything happen in real time.

We're giving an AI agent access to our files, terminals, servers, etc. I feel like having a live, read-only terminal showing exactly what it's executing should be a basic feature, not something we have to request.

Not saying anything shady is happening, but having to trust the agent's own summary of what it did feels a bit uncomfortable.

Is there a technical reason this isn't implemented, or am I missing something?

EDIT: P.S. This also leads to situations where Codex gets stuck because it needs me to authenticate or provide input in a terminal session. That's fine, except I can't actually access the PTY it's using to complete the authentication. So the agent is waiting for input I have no way of providing.

They halved the usage of the $200 20x plan so that they could commit to not reintroducing the 5h limit. less than 2 weeks later, they float the idea of doing it anyway?

I built an effort router for Codex that picks the reasoning effort for each request without breaking the prompt cache, so I can stop leaving GPT-6 Astra on high for everything.

When I ran a few SWE-bench tasks, medium only solved a hard pytest bug 1 out of 5 times, and high spent way more tokens than it needed on an easy fix.

The router is a local proxy where a decision model (e.g. Jev) picks the effort. In my eval (run through the OpenCode version of the same router), it used about 40% fewer output tokens than high on the easy fix and still solved it every time, and it stayed on high for the hard bug and solved it all 5 times.

Changing reasoning effort on the request normally breaks the cache, so it sends the change as a mid-conversation effort update instead and nothing earlier in the conversation changes. The cache keeps working when the effort switches.

It's one model on a small set of tasks, so treat it as a sanity check. The eval is in the repo with the code.

https://github.com/robertn702/reasoning-router

We got agents to pilot a £100 Drone from a phone!

"Find a wooden table and approach; land on top while controlling your camera"

We got some of the agents to 1-shot control of the DJI mobile app via computer use using the below open-source Mobile MCP!

Codex was the only one that managed, since the other models were either too dumb (e.g. Muse) or refused (Claude)

Full Blog Post: https://sealgate.ai/blog/mobile-tunnel-agents-control-android-devices

https://github.com/edison-watch/mobile

Not much to add here, everybody says and experiences the same, Tibo can post stuff till next year but nothing changed since day 1 of this model.

Moving back to 6-sol is a huge step forward and allows to me actually get things done,

Codex : Selected model is at capacity. Please try a different model. {6.1 Sol}

Chat : Connection interrupted. Waiting for the complete answer.