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Claude Opus 4.7

anthropic.com

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Re: Claude Opus 4.7

#31

I'm not sure how much I trust Anthropic recently. This coming right after a noticeable downgrade just makes me think Opus 4.7 is going to be the same Opus i was experiencing a few months ago rather than actual performance boost. Anthropic need to build back some trust and communicate throtelling/reasoning caps more clearly.

They don't have enough compute for all their customers.

OpenAI bet on more compute early on which prompted people to say they're going to go bankrupt and collapse. But now it seems like it's a major strategic advantage. They're 2x'ing usage limits on Codex plans to steal CC customers and it seems to be working.

It seems like 90% of Claude's recent problems are strictly lack of compute related.

Re: Claude Opus 4.7

#32

I just subscribed this month again because I wanted to have some fun with my projects. Tried out opus 4.6 a bit and it is really really bad. Why do people say it's so good? It cannot come up with any half-decent vhdl. No matter the prompt. I'm very disappointed. I was told it's a good model

Because it was good until January 2026, then it detoriated into a opus-3.1. Probably given much less context windows or ram.

Re: Claude Opus 4.7

#33
post #22
post #13

Introducing a new upgraded slot machine named "Claude Opus" in the Anthropic casino. You are in for a treat this time: It is the same price as the last one [0] (if you are using the API.) But it is slightly less capable than the other slot machine named 'Mythos' the one which everyone wants to play around with. [1] [0] https://claude.com/pricing#api [1] https://www.anthropic.com/news/claude-opus-4-7

If you're building a standard app Opus is already good enough to build anything you want. I don't even know what you'd really need Mythos for.

You'd be surprised. With React, Claude can get twisted in knots mostly because React lends itself to a pile of spaghetti code.

Re: Claude Opus 4.7

#34
Honestly I've been doing a lot of image-related work recently and the biggest thing here for me is the 3x higher resolution images which can be submitted. This is huge for anyone working with graphs, scientific photographs, etc. The accuracy on a simple automated photograph processing pipeline I recently implemented with Opus 4.6 was about 40% which I was surprised at (simple OCR and recognition of basic features). It'll be interesting to see if 4.7 does much better.

I wonder if general purpose multimodal LLMs are beginning to eat the lunch of specific computer vision models - they are certainly easier to use.

Re: Claude Opus 4.7

#35

I just subscribed this month again because I wanted to have some fun with my projects. Tried out opus 4.6 a bit and it is really really bad. Why do people say it's so good? It cannot come up with any half-decent vhdl. No matter the prompt. I'm very disappointed. I was told it's a good model

because they’re using it for different things where it works well and that’s all they know?

Re: Claude Opus 4.7

#36

> Opus 4.7 uses an updated tokenizer that improves how the model processes text. The tradeoff is that the same input can map to more tokens—roughly 1.0–1.35× depending on the content type. caveman[0] is becoming more relevant by the day. I already enjoy reading its output more than vanilla so suits me well. [0] https://github.com/JuliusBrussee/caveman/tree/main

I hope people realize that tools like caveman are mostly joke/prank projects - almost the entirety of the context spent is in file reads (for input) and reasoning (in output), you will barely save even 1% with such a tool, and might actually confuse the model more or have it reason for more tokens because it'll have to formulate its respone in the way that satisfies the requirements.

Re: Claude Opus 4.7

#38

Too late, personally after how bad 4.6 was the past week I was pushed to codex, which seems to mostly work at the same level from day to day. Just last night I was trying to get 4.6 to lookup how to do some simple tensor parallel work, and the agent used 0 web fetches and just hallucinated 17K very wrong tokens. Then the main agent decided to pretend to implement tp, and just copied the entire model to each node...

Funny because many people here were so confident that OpenAI is going to collapse because of how much compute they pre-ordered.

But now it seems like it's a major strategic advantage. They're 2x'ing usage limits on Codex plans to steal CC customers and it seems to be working. I'm seeing a lot of goodwill for Codex and a ton of bad PR for CC.

It seems like 90% of Claude's recent problems are strictly lack of compute related.

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