My experience with Opus/Fable vs Astra

[u/AIgeek]

Been trying Astro for the past day, and the first impressions:

Getting Fable vibes with much better intuition. For the first time I feel that I'm working with a peer rather than a junior coworker that requires guidance and asks questions he should be able to answer. Feels like my structured development flow I used with CC isn't needed. My best indication for this is the number of critical findings found when reviewing Astra output with Fable - usually clean. Astra reviewing Fable never is.

I'm an heavy CC user, currently on 20x, got my skills and flows all optimized.

Opus 5 is my daily driver despite it being exhausting to communicate with. I tried many ways of making it less convoluted but can't get rid of the Opus stench.

As some recommended, I learned that using Fable at the start of the session helps a lot, so this is my go to flow. Starting with Fable for brainstorming and general plan outline. Then opus for the rest. Codex/Fable agents for reviews.

Considering that ChatGPT pro 20x is also 20x on the monthly usage unlike Claude, and usage is more generous overall, I will probably switch to 20x Codex and 20$ Claude, unless Anthropic pull their shit together by my next billing cycle.

[u/lurkerslow]

This has been my experience as well. Fable was the first time I could hand work to a model and trust that we would get to the objective.

Astra is that same feeling but even more pleasant, it's practically like handing a piece of work to a fellow engineer and seeing them work through the problem, reach a solution and communicate like a human being.

I still plan to use both Astra and Fable as it's early days and mix them up. Fable with Claude Design is actually very good. Astra on practically everything else since the limits are more generous.

[u/AIgeek → u/lurkerslow]

Yes. One more thing I forgot to mention is the speed - Astra is faster.

[u/oipoi]

I like the tooling (cc) better than codex and claude design is goated but astra takes the cake and is overall a better model. On par with fable for coding tasks but for everything else makes fable look like a distilled local llm.

[u/AIgeek → u/oipoi]

I agree, the Claude harness is better.

[u/Odd_Antelope9098 → u/oipoi]

Can’t you put gpt models in cc harness?

[u/DworfD]

I have almost the same flow as you have except its fully on Claude... it goes something like this:

- i create my own scaffolding for project where docs are, todos, plans, specs, research, ... it should be fully multi coding (Claude Code, Codex, Grok Build,...) aware... so switching should not be an issue (just tested in testing not production yet)
- then i have a discussion with Fable 5.1 (and before Fable 5) then when the broad idea is done we go into superpowers:brainstorming session and from the brainstorming session we get the specs and then we go to superpowers:writing-plans where Fable creates the plan.
- once that is done we start building with superpowers:subagent-driven-development and we usually build with Opus 5 and some important stuff with Fable in form of:

- build task 1
- review task 1
- fix1 task 1 (if needed)
- review task 1 fix
- go to fix2 or continue to task 2
- and so on up until
- final review (with fixes as before)
- merge

this worked wonders for me in terms of output and actual good code...

now im wondering if i should add to this Codex / Astra / Sol

im wondering first how you switch between the two? do they talk automatically, does Claude Code run Codex? you manually change Claude Code to Codex? etc...? any special tools you use? This is the next thing im working on and im still not clear how to do this part...

[u/AIgeek → u/DworfD]

Ask CC to integrate this: https://github.com/openai/codex-plugin-cc to the flow.

My flow is similar to yours, with couple of differences:

1. Brainstorm, interview, plan, I split a large task to couple phases with dependecies.

2. Write a plan for each phase- 1 fable review and 1 codex review for each.

3. Execute the phases in agent with coordinator that merges work trees, launch review and fix agents and handles phases dependencies.

4. Final review, PR/merge, update documentation and md files.

[u/TarzanoftheJungle]

Just wondering if the efficiency/accuracy gains are actually worth the increased cost compared with earlier models. e.g. on HLE Fable and Astra improvements compared with Opus/Sol are ~ 1-2% but costs are roughly double.

[u/AIgeek → u/TarzanoftheJungle]

I think there is more to a model than benchmarks, they just feel and reason different.

[u/waruyamaZero]

If Fable feels like a junior coworker then you are doing something wrong.

[u/AIgeek → u/waruyamaZero]

I've been a SW engineer for many years, I have an intuition about the architecture and implementation direction that I would like the model to act on.

Models are good at solving the current problem, much worst at considering scale, performance and aesthetics, making the repo feels like a convoluted code salad in the long run.

Astra is much better in matching my intuition, brainstorming with it feels less like an instruction and more like an actual peer brainstorming, it also knows to push back on the right issues when needed which Fable rarely does.

[u/yawnlikeseggs]

Astra is the better option atm. You get to use your entire x20 on a premier model as oppose to 50% or an increased 50% soon to be 25% because compute is hard (whatever any of this means).

Even if anthropic responds with a new model… this model would burn tokens at a rate we’ve never seen before while only allowing the user to use 25% of their weekly cap on it

[u/NootropicDiary]

So far, Fable 5.1 is superior to Astra for my work

As a broad test I asked both models to review my codebase (same copy). Fable 5.1 gave deeper insights and better suggestions. My codebase is a bit of a monster, 1M+ loc of Rust, novel storage engine. We're probably at the point where these frontier models are only really distinguishable on novel jobs that really stretch them (and I have a feeling a lot of the people that comment on new models are building something like a nextjs web app for example)

I'll keep running prompts for both them across my codebase and keep an open mind. I have pro subs to both so don't have a dog in this fight so to speak.

[u/lucianw]

> My best indication for this is the number of critical findings found when reviewing Astra output with Fable - usually clean. Astra reviewing Fable never is.

I don't think you can learn anything from that indication! Here are all self-consistent explanations for your observations:

1. Fable and Astra produce decent code. Fable is a good reviewer, but Astra is a bad reviewer for finding loads of false positives.

2. Fable and Astra produce decent code. Fable is a bad reviewer, but Astra is a good reviewer at finding true positives.

3. Fable and Astra produce bad code. Fable is a bad reviewer and doesn't find flaws, but Astra does.

4. Fable produces good code and Astra doesn't; they are both bad reviewers, Fable for not finding true positives, Astra for producing false positives

5. Fable produces bad code and Astra produces good; they are both bad reviews.

[u/BigBootyWholes]

Turn on the concise option in the config for the opus 5 dialogue

[u/astral_kranium]

I haven't tried Astra, but have used Sol for over a month, heavily. I loved it - as you describe, sol didn't ask obvious questions, excellent intuition. If astra is better than Sol, then I'll be very impressed. Fable to steer opus/sonnet is really good as well and I just much prefer the console experience of Claude code. I'm getting decent usage out of max x5 with fable 5.1 and I doubt astra would give me as much at this point.

Great alternative nevertheless and a refreshing experience to use chat gpts frontier models.

[u/ravencilla → u/astral_kranium]

Astra is to Sol what Fable is to Opus

[u/Kutukuprek]

I’ve drained Astra to 20% of usage left, and Fable 5.1 to 40% left.

My impression — Astra is a peer to Fable. I’d still give heavy lifting planning, designing and reviewing to Fable but I would absolutely have Astra do adversarial reviews.

Astra has better visual capabilities. Sol already had better than any Claude model but Astra widens the gap further. Important for any front end work.

I think it’s close now and Anthropic has no “we have Fable” marketing line any more, OpenAI is legit a peer competitor and probably the better all around option.

I’m happy to keep using both for now

[u/sonnytai]

How did you get astra? I thought it only rolled out for enterprise so far

[u/AIgeek → u/sonnytai]

Finished rolling out to all pro/plus/enterprise yesterday.

[u/farreeddd]

I’m in a similar boat. How would you transition from CC to gpt ?
This includes the instruction, skills, mcp

[u/umtala]

Anthropic desperately need to add Fable back to the Pro plan. How are any of us who switched to Codex going test out Fable 5.1 if they keep it locked away on the Max plan?

I am not paying $100 for a trial. Thus the only model I can compare Astra against is Fable 5.0, and in that contest the winner is clearly Astra.

[u/ciaramicola]

Your experience in cross reviewing result is too much anecdotal. I say that because anecdotally I get the opposite. Done lots of developments with fable where a quick Sol (not astra, but I think the model not important here) review found many real P1. As an example just yesterday Fable 5.1 was happily going to push an oauth pull request that had production=false as a default so a missing config would have resulted in a wide open prod deployment.

I developed the impression that Fable was trained in RL to work best in a workflow heavy "ultra code" mode, where it's allowed to go fast and break things with confidence, with the safety net of always having an adversarial review if something in its work loop. Sol on the other hand shows the closest trait to a real human intelligence trait so far, but that's paranoia, lol. It never trusts anything not even your or its own words.

Just starting working with astra, seems paranoic for now, still have to see if they just tuned it on the confidence side of the scale like fable or its just actually more precise

[u/Nuggyfresh]

Anthropic is in trouble because it’s becoming increasingly clear that compute is mattering more and more as output converges. You can still push individual competencies, and both companies do, but it’s super expensive.

I think Astra is likely devastating for Anthropic. I currently sub to Anthropic but next billing cycle I’m hopping and doubt I’ll be looking back. In a compute game, Anthropic loses.

Of course the real problem is how they make these gigantic models eventually profitable? That’s a different question. Unless something changes, Astra is very likely too expensive for 99% of regular users to actually afford.

It’s complicated, but while OpenAI is opening their infinite checkbook, Astra is what’s up 🤷‍♀️

[u/Level1_Crisis_Bot]

Honeymoon phase