U.S. government will decide who gets to use GPT-5.6 - https://news.ycombinator.com/item?id=48690101

"We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed. Access will initially be limited to select customers as we expand capacity."

750 tokens/s on a frontier model is going to be extremely interesting. I doubt this new version is anything but a version bump in terms of capabilities but if we can start getting these answers back faster, they end up being more useful.

Just off the top of my head, I can think of the tedious task of finding certain functionality within a codebase. I usually can't beat an AI agent harness at this task today. If the AI model is 3x faster I have less of chance.

- GPT-5 mini costs $0.25/$2 and will be discontinued in December.

- GPT-5.4 mini costs $0.75/$4.5 and is supposed to be the replacement.

- GPT-5.4 nano costs $0.2/$1.25 and, while it ranks better in benchmarks than GPT-5 mini, it's not even close when you test it in real scenarios.

So you're left being forced to go to GPT 5.4 mini if you use 5 mini today.

The same thing is happening here as their “Luna“ model will cost $1/$6.

Can't we just stay with the models we actually want? I don't need GPT 5.4 mini. GPT-5 does the job.

Maybe it’s the realization that it was never that cheap in the first place and they're forcing us to upgrade in a slow and painful way.

https://metr.org/blog/2026-06-26-gpt-5-6-sol/

Recently, I went head-to-head with GPT on nearly 2,000 lines of code, and GPT's solution was superior and faster. I even referenced multiple codebases on GitHub while trying, but they were incomparable to GPT.

So using GPT brings both fear and excitement.

The fear comes from realizing that this level of code is now the average for most people. The excitement comes from knowing that I can now study and learn at this level too.

I'm really looking forward to seeing how much more advanced the code will be with the upgrade to 5.6.

I've been running some tests on a harness we're building, and suddenly saw a jump in a few points yesterday. I reran the vanilla codex benchmark and saw an ~88% score on Terminal Bench 2.1 from GPT-5.5 on vanilla Codex.

The biggest indicator, beyond the score, was that 3 tests which frequently hit "safety" blockers with 5.5 started succeeding last night without warning.

I'm curious about how does this work? Do the subagents also get to use the same tools? Will the client be flooded with tool calls? Why extra pricing for a new "model" when the same thing can happen in the client with more controls?

And if it's an army of subagents, why do they compare it to Fable and Mythos? Those models with similar harness would probably bench better I'm guessing

This is like advertising the latest achievements during Space Race, when Johnny just wants a Space Helmet and “friendly futuristic AI robot helping humanity, glowing blue eyes, white glossy body, holographic interface, floating transparent screens, digital particles, neural network background, cinematic lighting, volumetric god rays, ultra detailed, hyper realistic, 8K, masterpiece, award-winning, octane render, Unreal Engine 5, ray tracing, sharp focus, dramatic composition, vibrant blue and purple color palette, futuristic technology, innovation, hope, smiling business professionals, depth of field”

To me that means “it’s an inferior product but marketing dictates we try and hide that.”

And “our most robust safety stack to date. We strengthened protections for higher-risk activity, sensitive cyber requests, and repeated misuse, and spent multiple weeks finding weaknesses, pressure-testing our system, and hardening it against real-world attacks” is of zero value to me at best, and most likely to my detriment (increasing refusals or nerfing utility). Why do providers keep leading with that? Are there customers (besides support ChatGPT chatbot users, maybe??) that ask for this?

This seems like it would be the largest and first closed-source model Cerebras has offered till date

So the next naming scheme might be FTX, Madoff and Enron? :^)

This is really exciting. I work on voice AI, and we're still using 4.1/4.1 mini since none of the frontier models come close on latency. I'm excited to be able to have more interactive experiences, I think it'll unlock new ways of working with these models.

Agent Arena (Dynamic ranking of models on how well they orchestrate tools for real-world agentic tasks, based on signals like tool reliability, task completion, and steerability.)

Top 10, Highest rank to lowest

Claude Fable 5 (High), Claude Opus 4.8 (Thinking), GPT 5.5 (xHigh), Claude Opus 4.7 (Thinking), GPT 5.5 (High), Claude Opus 4.7, Claude Opus 4.6, GPT 5.5, GPT 5.4 (High), GLM 5.2 (Max)

Text Arena View overall rankings across various AI models in text-to-text tasks across math, coding, creative writing, and other open-ended domains.

Top 10, Highest rank to lowest

claude-fable-5, claude-opus-4-6-thinking, claude-opus-4-7-thinking, claude-opus-4-6, claude-opus-4-7, muse-spark, gemini-3.1-pro-preview, gemini-3-pro, claude-opus-4-8-thinking, gpt-5.5-high

I'd really like to see other companies like Chinese ones compete at this level.

Pricing on GPT 5.5 is already super high and having more competition can only help :)

But GPT-5.5 is as useful an LLM can be; it has solved lemmas I've thought about for a year, it can implement typed STLCs in Rust when I give it a formal grammar, it can help me analyze Postgres planner dumps.

It's great at tasks that have short solutions but

- they cannot learn based on a project

- their long term planning capabilities are worse than worms

- they are unconfident in decision making

- their internal representations are disgusting compared to JEPA

- they don't have any "system clock" like humans and computers do

- LLM architecture is not modular like computer architecture or human brain architecture

There's so many issues with LLMs. I wish that companies can start working on the next generation of architectures before the bubble pops

>>During this preview, we will continue testing and coordinating closely with partners as we work toward broader availability.

Instead of generating negative publicity, can't they just wait for the preview period to get over?.

What does openAI announce when they know others can't access it?. Curious question - what do they gain from this?

If it was the next generation, why isn't it a major version change..?

Are we starting to see the 'we just realized that 100,000,000 GPU's later, 2+2 isn't the magic number, no matter how many times we calculate it' hit home?

A while back I gave the same task to both, and Codex used 20x less of my 5-hour limit (both on the $20/month plan).

(This annoyed me since I tend to prefer Claude, but the limits at the time made it unusable for anything serious.)

However, since that time, both providers have massively reduced usage allowances (and at least one of them has gotten sued for it, lol).

I'm not currently subscribed to either but I'm weighing my options. With GPT being slightly better than Opus, and it used to have way higher limits, I'm leaning in the direction of an OpenAI sub. But I'm wondering if the current state matches my memory from 2-3 months ago. (Since both companies appear to be cost-cutting hard!)

Prefer responses from people who use both, but anecdotes welcome :)

Thanks!

basically

I hope this means then fable will also get released again.

If this is the new norm, we as workers should all start look for jobs in those companies.

Who knows what they will fix, block or change in the model between the preview and GA time. Open models can't arrive soon enough.

The clowns in the US administration can barely remain coherent from one sentence to the next.

Having them be the gatekeepers of technological progress in 2026 is fucking lame.

I'm looking at you Codex.

I mean, you can read them even without the colors, but who on earth thought that those are a good set of colors? Oh, I forgot it was probably someone on 'Sol'.

Doesn't that undermine all good-faith discourse on cybersecurity safeguards, controlled usage etc? Or is that overstating the case (I'm not a security researcher myself so kinda parroting).

Is it just me, or does it seem like Anthropic has been more of a pioneer the past few years, and OpenAI tries to copy features they like?

    we expect substantial benefit for legitimate defensive work, while meaningfully constraining prohibited offensive use.

Also just making the model better at code is just making it better to writing offensive code.

> GPT‑5.6 is priced per 1M tokens across three model sizes:

> Sol is $5 input / $30 output;

> Terra is $2.50 input / $15 output

> Luna is $1 input / $6 output.

The OpenAI casino has never been more ready to take your money on gambling even more tokens.

https://news.ycombinator.com/item?id=48678789

https://news.ycombinator.com/item?id=48683021

Anyone know the latest around Fable being re-released after gov smackdown?

1. Naming convention is copied from Anthropic and honestly is more catchy than a number (amongst normal people)

2. How in the world did Anthropic have to do all the theatrics about Mythos just to have OpenAI release an equivalent or stronger model a month later without any drama???

3. Cheaper models are just don’t fit any usecase imo and OpenAI knows it so they keep increasing the floor - I’m still convinced task per capability is reduced with each release

4. How in the world would open source models keep up with the multi layer security? Either this security is all theater or we will finally see a ceiling in open source models because by definition they can’t have those protections

5. Cybersecurity things are boring to me because it’s all zero sum cat and mouse games

I mean, if they deem Fable 5 to powerful to share with the rest of the world, what's left for us?

Sol Ultra ≈ Pro

Sol ≈ Standard

Terra ≈ Mini

Luna ≈ Nano

Not them joining Anthropic with this bullshit. *

Caching infrastructure is already a leaky abstraction over a feature that is not as reliable or debuggable to the end user as it should be, charging for the 'privilege' of interacting with it is really annoying.

(* for reference on 'this bullshit': ChatGPT previously didn't require anything special for a basic level of caching. Unless you wanted extended cache times, it'd just "do the right thing" and try to use nodes that had your prefix already cached in memory)

    Flagged activity can also trigger account-level review across relevant conversations and risk signals, consistent with our terms and policies around content retention and review. Looking beyond a single conversation helps our systems distinguish persistent malicious behavior from legitimate dual-use security work, where similar technical concepts may appear in very different contexts.

Every conversation you have with these "more capable" models will be monitored and joined up and then your entire account might one day be tagged as Distiller or Cyber Threat Actor or whatnot. When combined with identity verification (which isn't discussed in this press release), expect people to be falsely flagged and banned from ever using OpenAI models again.

Wish I could find the thread from last week where discussions of exactly this kind of thing were dismissed as daft and outlandish.

Now they've got friendly cosmic names. And this time they want us to believe that this time they're gonna stick to a naming convention? I'll believe it when they do 3 releases in a row without inventing a new naming scheme.

https://pbs.twimg.com/media/HLwuJLvbwAAOfQZ?format=jpg&name=...

  * House design plans from prompts
  * Government surveillance of public communication
  * Extracting world/spatial concepts from language models (do we really need a world/spatial models now?)
  * Driverless City planning startups
  * Election vote rigging/harvesting startups
  * Video game NPC backstory startups (all NPCs in GTA 6 go to work, go home, shower, go to sleep now?)