Not surprising considering Grok 4.7 is a 2T model, so Sol/Opus class, not Astra/Fable class.
replyHow many parameters do Astra or Fable have?
reply5T I believe is the guess, though not sure its public anywhere.
replyI believe most speculation is that Opus is 5T model, Fable a 10T
replyElon claimed Opus was 5T in April, and I think it's fairly likely this is accurate: https://x.com/elonmusk/status/2042123561666855235
Astra fails in similar ways, and at similar frequency, as GPT 5.6 Sol does. It often goes way out of scope, or just stops prematurely, or tries to find odd and even dangerous workarounds when it gets stuck.
replyIt's phenomenal at computer use and 3D stuff. I've been using it less and less for coding.
Same, Astra is extremely RL fried, and nobody is talking about it. I used Astra for a few days on my personal project, and load times went from less than 3 seconds to almost 30 seconds because it kept using the wrong sync primitives and bad architecture overall.
replyHuh, I've had a totally different experience.
I've used it extensively, maxing out the 200€ plan on personal projects and it's the best model I've ever used, so easy and pleasant to use.
It's great for frontend design and using it in Rust I've had
Coming from Opus 5, it's a breath of fresh air.
replySame experience. Astra is on par with or better than Fable 5.1 with a lot more usage on the plans. It has been an extraordinary experience using it so far. 5.6 Sol was very good and Astra is a large upgrade in quality.
replySame. GPT-6 has been a huge breath of fresh air for me. Fixed 80% of the issues I was having with Sol. I just gave it the same task I gave to Sol a few months ago, and it knocked it out of the park comparatively.
replyLLM's introduces problems, and it finds them in its own internal thinking. But instead of actually modifying the previous generated answer to fix the real issue, it adds another layer to deterministically guard around it, greatly expanding the scope of the fix. This scales with effort, and the result is spaghetti and with a side of bugs.
replyBest to stick with a high end model + low effort, do a manual pass on high effort and fix the bugs you know are reachable.
It's really interesting how different the experience people have is with these models. I tried Codex with whatever they had before Sol and then with Sol, and just kept going back to Claude Opus/Fable because they were better at the coding work I was doing. Despite getting annoyed at the way it replied/wrote, it was just much better. Astra is the first one that feels as good as Fable to me, and it's much less annoying in its replies. I still don't think they have anything I'd want to drop down to like I can drop down to Opus though.
replyyeah I see this in these threads, I'm guessing the user prompts are the actual wildcard, it has been for my use thats for sure. edit: I wonder if gemini is somehow training me to like it more lol
replyI don't understand these comments.
replyThe two models are in completely different price tiers. Astra costs 5 times as much.
It seems like all you can judge about cars would be their maximum speed on an oval.
If you have a look at their headline benchmark on the post here, Grok 4.7 is hardly cheaper than Fable 5.1 Low and performs similarly.
replyBased on Artificial Analysis Cost per Task, Astra is about 2-3x cheaper than Fable 5.1 at Medium and Low.
Consequently Astra could be cheaper than Grok 4.7, depending on the task.
I tried Astra w/ high reasoning on a design document project and it was horrible. It started duplicating output lines, made document edits without permission, and basically did a poor job writing clear prose. I went back to 5.6-sol and it's great. I'm an OpenAI fanboy and was severely disappointed. I hope Astra is better for coding.
replyNo, Astra isn’t better for coding. I’ve switched back to Sol.
replyIn programming I mostly use AI for Godot/GDScript code reviews, plus suggestions, and Astra is so much better than everything
replySame here with Godot. I was impressed that it could make an entire working project in one shot
replyI agree, the models keep getting better at one shotting. That’s useful in a lot of situations, like for small one-off scripts that filter/transform some tool call, or make a clever bash call. For the code itself, it doesn’t help me much though.
replySadly "one-shotting" is the only thing most "AI reviewers" and their audiences on YouTube seem to understand.
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