I am sorry, I meant to say I generated STAR out of my resume line, trying to generate STAR, and polish it thus $5.

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I provided crapton of context for that one resume line. All the work I did, documentations for my justifications, etc.

I initially messed up and came out ot $5, rest of resume used around $4 per line (I used a fresh new session on purpose).

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As a clarification, $2.2 average for OPUS 5.5 was the same process in a new session, same context, same prompts.

Also adding verification for that Fable 5.1 output in the same sesssion.

Retiring the Terra tier? Their space-inspired lineup has only been out for 2 months, they're already messing with it?

I personally use up to 3 models. Fable/Opus for planning, Opus/Sonnet for implementation depending on complexity.

I would maybe use Haiku 5.5 for highly parallel workflows like checking in on MRs or scanning my entire codebase.

Terra lost to Sol and Luna at every cost/performance point, it had no reason to exist.

New generation's "upper-mid tier" offering claims to be almost 1:1 match for the previous gen's "top tier" - in other news, fork found in kitchen.

Now, Anthropic might stall on releasing Fable 5.5, due to the "pacing the frontier" threat-to-humankind management business. If so, Fable 5.1 would remain a niche model for the next bit.

That's not my experience at all. Opus is an extremely capable coder on high or xhigh effort. It can read academic papers, implement algorithms from the description in the paper alone and reproduce results without breaking a sweat. This is remarkable because it is pure reasoning on unseen material; in some cases the paper was just published and there wasn't an implementation to learn from in the training data.

Opus is fine at coding (for correctness), but horrible at talking about code. I don't really see the defect rate going down when using Astra or Fable 5.1, but they are just more coherent in both how they explaing code/architecture/choices, and how they actually code the thing. With Opus, I'm using smaller models to delete the vast majority of comments and 'clean up' correct code that is too weird.

Thing is, I'm still reading the majority of generated code, and I have colleagues who'll laugh at me if my PRs are a shit show. I fear what vibe coders are pushing to the servers of myriads of start ups, and pity the poor people who'll have to clean it up in a year or two.

Mines pretty much inverted - my colleagues and I noticed almost zero difference between the quality of code in Opus vs Fable. Occasionally I'll switch to Fable for an arduous debugging task but that's about it.

isn't this what mythos was/is?

I've done GLM 5.3 previously here: https://news.ycombinator.com/item?id=49295420

Worth noting though that GLM 5.3 isn't multi-modal, so it doesn't have a vision layer. It is quite clever and hacks around it pretty effectively however. I'm running a deepseek 4 build now and will reply shortly with that.

The designs are outputs from my own site. This has an overview of the process: https://diffui.ai/learn/new-site

The gist of it though is I take a prompt, expand it into a json blob specifying structure/palette/positioning of elements/etc, feed that into a diffusion model to output a few choices. Once I lock in a choice I take the pixel output + json blob and use it as input into followup pages. The json helps preserve the brand across multiple pages.

Once I have all the inputs I take their corresponding image+json blobs and feed them into an agent to create a web implementation.

For image models, diffui currently uses gpt-image-2.5, mai-image-2.6, and very, very rarely a post-trained version of flux 2 dev I've made for web design, though that one will be deprecated soon.

And here's the important part...

you win the thread

Wrong century, brother.

Anthropic is absurdly vague about 3rd party harnesses for subscriptions, if you try to use anything besides Claude Code, you are likely at risk of getting banned, you can "do it", but are at their mercy if they decide to ban you. OpenAI gives their blessing to using oauth on any harness, you can make your own or use any of the popular public ones like opencode, pi, whatever exe.dev is that this guy mentioned.

So in simple terms, OpenAI doesn't restrict you to Codex, and gives their blessing to try whatever you want with their models(besides serving others with your subscription usage, that is still afaik against tos).

Per the link someone else posted, the actual difference in $/task is not nearly so stark:

https://artificialanalysis.ai/models/releases/claude-opus-5-...

  Opus 5.5 Medium = $1.34
  GPT-6-Astra High = $1.76

And that assumes Opus 5.5 Medium is actually equivalent to Astra High in all real-world usage/personal work loads, which isn't guaranteed as benchmarks saturate. The High vs. High comparison (probably not equivalent, but for reference):

  Opus 5.5 High = $1.82
  GPT-6-Astra High = $1.76

If Opus 5.5 Medium isn't equal/better for what you're working on vs. Astra High across the board, the price difference would narrow a bit more each time you had to switch to High.

So, if you're happy with Codex already it's not like Opus is now 1/2 the price and you'd be leaving a crazy amount of money/tokens on the table. Plus you have way more flexibility on the low end of the intelligence curve with GPT 5.6 Luna: Haiku (and Sonnet) can't touch that price/value ratio.

In the end what matters is how much you pay for the task you want completed. And Astra will usually do that using less token and offer a better quality solution so in the end it might be cheaper.

yeah, Astra burned through 70% of my weekly usage in ~5hrs on a $100 plan. even fable doesn't run out that quickly for me. it's great, but it's on the same tier as fable for me - use it sparingly, only when really necessary.

> Even on a subscription you'll get considerably more usage out of Opus.

That's an incredibly bold assumption.

news to me as well. i thought you were forced to use Codex if you wanted their subscription. I completely ignored it because of that. How do we do it?

I read the page. It seems like a marginal improvement.

Let's wait for independent benchmarks at least

Better than what? Deepseek? GLM? Gemini 3.8?

Not the same person but... nothing. Haiku just hasn't been an interesting model for a long time. If you want cheap and fast, there are lots of options that are simultaneously cheaper, faster, and capable than Haiku.

I use it for executing well-prepared plans sometimes. And for exploring larger codebases.

bro why. its literally the most overpriced model in existence right now. i could name about 10 models off the top of my head that would be better and cheaper

And not fable lol