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Claude Opus 4.5

anthropic.com

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Re: Claude Opus 4.5

#511

Post by CryptoBanker »

Stevvo wrote: post #127
bnchrch wrote: post #5

Seeing these benchmarks makes me so happy. Not because I love Anthropic (I do like them) but because it's staving off me having to change my Coding Agent. This world is changing fast, and both keeping up with State of the Art and/or the feeling of FOMO is exhausting. Ive been holding onto Claude Code for the last little while since Ive built up a robust set of habits, slash commands, and sub agents that help me squee…

With Cursor or Copilot+VSCode, you get all the models, can switch any time. When a new model is announced its available same day.

You don't get any reasoning with Copilot

Re: Claude Opus 4.5

#512

Post by docjay »

threeducks wrote: post #239
docjay wrote: post #189

Earlier quoted context omitted.

That all depends on what you consider to be reasonably running it. Huge RAM isn’t required to run them, that just makes them faster. I imagine technically all you'd need is a few hundred megabytes for the framework and housekeeping, but you’d have to wait for the some/most/all of the model to be read off the disk for each token it processes. None of the closed providers talk about size, but for a reference point of t…

> (~1TB / SSD_read_speed + computation_time_per_chunk_in_RAM) = a few minutes per ~word or punctuation. You have to divide SSD read speed by the size of the active parameters (~16GB at 4 bit quantization) instead of the entire model size. If you are lucky, you might get around one token per second with speculative decoding, but I agree with the general point that it will be very slow.

Yeah thanks for calling that out. I kind of panicked when I reached that part of the explanation and was stuck on whether or not I should go into dense models vs MoE. The question was about ‘big stuff like that’, which they most certainly use MoE, then I even chose an MoE as an example, but then there are giant dense models like Llama, but that’s not what was asked, although it wasn’t not asked because ‘also big league stuff’…anyway, I basically thought “you’re welcome” and “no problem”, then said “you’re problem”.

Re: Claude Opus 4.5

#514

Post by stingraycharles »

mopierotti wrote: post #490
stingraycharles wrote: post #478

Earlier quoted context omitted.

All those are completely irrelevant. Quantization is just a cost optimization. People are claiming that Anthropic et all changes the quality of the model after the initial release, which is entirely different and the industry as a whole has denied. When a model is released under a certain version, the model doesn’t change. The only people who believe this are in the vibe coding community, believing that there’s some…

I might be misunderstanding your point, but quantization can have a dramatic impact on the quality of the model's output. For example, in diffusion, there are some models where a Q8 quant dramatically changes what you can achieve compared to fp16. (I'm thinking of the Wan video models.) The point I'm trying to make is that it's a noticeable model change, and can be make-or-break.

Of course, no one is debating that. What’s being debated is whether this is done after a model’s initial release, eg Anthropic will secretly change the new Opus model to perform worse but be more cost efficient in a few weeks.

Re: Claude Opus 4.5

#515

Post by [deleted] »

enraged_camel wrote: post #350
sothatsit wrote: post #290

Earlier quoted context omitted.

The benefit you get from juggling different tools is at best marginal. In terms of actually getting work done, both Sonnet and GPT-5.1-Codex are both pretty effective. It looks like Opus will be another meaningful, but incremental, change, which I am excited about but probably won’t dramatically change how much these tools impact our work.

It’s not marginal in my experience. Once you spend enough time with all them you realize each model excels at different areas.

[deleted]

Re: Claude Opus 4.5

#516

Post by teruakohatu »

ChadNauseam wrote: post #405
teruakohatu wrote: post #397

Earlier quoted context omitted.

> 1. The nerf is psychologial, not actual. 2. The nerf is real but in a way that is perceptual to humans, but not benchmarks. They could publish weekly benchmarks. To disprove. They almost certainly have internal benchmarking. The shift is certainly real. It might not be model performance but contextual changes or token performance (tasks take longer even if the model stays the same).

Anyone can publish weekly benchmarks. If you think anthropic is lying about not nerfing their models you shouldn't trust benchmarks they release anyway.

I never said they were lying. They haven’t stated that they do not tweak compute, and we know the app is updated regularly.

Re: Claude Opus 4.5

#517

Post by arghwhat »

int_19h wrote: post #497
arghwhat wrote: post #445

Earlier quoted context omitted.

I could also decode it by hand, but doing so is stupid and will be unreliable. Same with an LLM - the network is not geared for precision.

You don't know what it's geared for until you try. Like I said, GPT-4 could consistently encode and decode even fairly long base64 sequences. I remember once asking it for an SVG image, and it responded with HTML that had an tag in it with a data URL embedding the image - and it worked exactly as it should. You can argue whether that is a meaningful use of model capacity, and sure, I agree that this is exactly the ki…

Sure you do, the architecture is known. An LLM will never be appropriate to use for exact input transforms and will never be able to guarantee accurate results - the input pipeline yields abstract ideas as text embedding vectors, not a stream of bytes - but just like a human it might have the skill to limp through the task with some accuracy.

While your base64 attempts likely went well, that it "could consistently encode and decode even fairly long base64 sequences" is just an anecdoate. I had the same model freak out in an empty chat, transcribing the word "hi" to a full YouTube "remember to like and subscribe" epilogue - precision and determinism are the parameters you give up when making such a thing.

(It is around this time that the models learnt to use tools autonomously in a response, such as running small code snippets which would solve the problem perfectly well, but even now it is much more consistent to tell it to do that, and for very long outputs the likelihood that it'll be able to recite the result correctly drops.)

Re: Claude Opus 4.5

#518

Post by arendtio »

827a wrote: post #12

I've played around with Gemini 3 Pro in Cursor, and honestly: I find it to be significantly worse than Sonnet 4.5. I've also had some problems that only Claude Code has been able to really solve; Sonnet 4.5 in there consistently performs better than Sonnet 4.5 anywhere else. I think Anthropic is making the right decisions with their models. Given that software engineering is probably one of the very few domains of AI…

I think the 'Agentic coding SWE-Bench Verified' [1] was actually the one benchmark where Google didn't even claim to beat Sonnet 4.5 ;-)

[1] https://deepmind.google/models/gemini/pro/

Re: Claude Opus 4.5

#519

Post by judahmeek »

thelittleone wrote: post #367
Aeolun wrote: post #297

Earlier quoted context omitted.

It’s important to note that with the introduction of Sonnet 4.5 they absolutely cratered the limits, and the opus limits in specific, so this just sort of comes closer to the situation we were actually in before.

That's probably true, but whereas before I hit max 200. Limits once a week or so. Now I have multiple projects running 16hrs a day some with 3-4 worktrees, and haven't hit limits for several weeks.

What kind of stuff are you working on?

Re: Claude Opus 4.5

#520

Post by throwaway-aws9 »

tekacs wrote: post #60
llamasushi wrote: post #30

The burying of the lede here is insane. $5/$25 per MTok is a 3x price drop from Opus 4. At that price point, Opus stops being "the model you use for important things" and becomes actually viable for production workloads. Also notable: they're claiming SOTA prompt injection resistance. The industry has largely given up on solving this problem through training alone, so if the numbers in the system card hold up under a…

This is also super relevant for everyone who had ditched Claude Code due to limits: > For Claude and Claude Code users with access to Opus 4.5, we’ve removed Opus-specific caps. For Max and Team Premium users, we’ve increased overall usage limits, meaning you’ll have roughly the same number of Opus tokens as you previously had with Sonnet. We’re updating usage limits to make sure you’re able to use Opus 4.5 for daily…

Thanks. I unsubscribed when I busted my weekly limit in a few hours on the Max 20x plan when I had to use Opus over Sonnet. It really feels like they were off by an order of magnitude at some point when limits were introduced.
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