One thing I didn't see mentioned is raw token gen speed compared to the alternatives. I am using Haiku 4.5 because it is cheap (and so am I) but also because it is fast. Speed is pretty high up in my list of coding assistant features and I wish it was more prominent in release info.
Claude Opus 4.5
181–190 of 525 posts
Re: Claude Opus 4.5
#182Earlier quoted context omitted.
I almost scrolled past the "Safety" section, because in the past it always seemed sort of silly sci-fi scaremongering (IMO) or things that I would classify as "sharp tool dangerous in the wrong hands". But I'm glad I stopped, because it actually talked about real, practical issues like the prompt injections that you mention. I wonder if the industry term "safety" is pivoting to refer to other things now.
I thought AI safety was dumb/unimportant until I saw this dataset of dangerous prompts: https://github.com/mlcommons/ailuminate/blob/main/airr_offic... I don't love the idea of knowledge being restricted... but I also think these tools could result in harm to others in the wrong hands
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Re: Claude Opus 4.5
#183Some early visual evaluations: https://x.com/mutewinter/status/1993037630209192276
Re: Claude Opus 4.5
#184This is gonna be game-changing for the next 2-4 weeks before they nerf the model. Then for the next 2-3 months people complaining about the degradation will be labeled “skill issue”. Then a sacrificial Anthropic engineer will “discover” a couple obscure bugs that “in some cases” might have lead to less than optimal performance. Still largely a user skill issue though. Then a couple months later they’ll release Opus 4…
With Claude specifically I've grown confident they have been sneakily experimenting with context compression to save money and doing a very bad job at it. However for this same reason one shot batch usage or one off questions & answers that don't depend on larger context windows don't seem to see this degradation.
Re: Claude Opus 4.5
#185Earlier quoted context omitted.
Now THAT is great news
From the HN guidelines: > Please don't use uppercase for emphasis. If you want to emphasize a word or phrase, put asterisks around it and it will get italicized.
There's a reason they're called "guidelines" and not "hard rules".
Re: Claude Opus 4.5
#186The 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…
What's super interesting is that Opus is cheaper all-in than Sonnet for many usage patterns.
Here are some early rough numbers from our own internal usage on the Amp team (avg cost $ per thread):
- Sonnet 4.5: $1.83
- Opus 4.5: $1.30 (earlier checkpoint last week was $1.55)
- Gemini 3 Pro: $1.21
Cost per token is not the right way to look at this. A bit more intelligence means mistakes (and wasted tokens) avoided.
Re: Claude Opus 4.5
#187Earlier quoted context omitted.
From the HN guidelines: > Please don't use uppercase for emphasis. If you want to emphasize a word or phrase, put asterisks around it and it will get italicized.
There's a reason they're called "guidelines" and not "hard rules".
I thought the reminder from GP was fair and I'm disappointed that it's downvoted as of this writing. One thing I've always appreciated about this community is that we can remind each other of the guidelines.
Yes it was just one word, and probably an accident—an accident I've made myself, and felt bad about afterwards—but the guideline is specific about "word or phrase", meaning single words are included. If GGP's single word doesn't apply, what does?
Re: Claude Opus 4.5
#188I've almost ran out of Claude on the Web credits. If they announce that they're going to support Opus then I'm going to be sad :'(
Re: Claude Opus 4.5
#189Does anyone know or have a guess on the size of this latest thinking models and what hardware they use to run inference? As in how much memory and what quantization it uses and if it's "theoretically" possible to run it on something like Mac Studio M3 Ultra with 512GB RAM. Just curious from theoretical perspective.
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 the scale: Kimi K2 Thinking can spar in the big leagues with GPT-5 and such…if you compare benchmarks that use words and phrasing with very little in common with how people actually interact with them…and at FP16 you’ll need 2.9TB of memory @ 256,000 context. It seems it was recently retrained it at INT4 (not just quantized apparently) and now:
“ The smallest deployment unit for Kimi-K2-Thinking INT4 weights with 256k seqlen on mainstream H200 platform is a cluster with 8 GPUs with Tensor Parallel (TP). (https://huggingface.co/moonshotai/Kimi-K2-Thinking) “
-or-
“ 62× RTX 4090 (24GB) or 16× H100 (80GB) or 13× M3 Max (128GB) “
So ~1.1TB. Of course it can be quantized down to as dumb as you can stand, even within ~250GB (https://docs.unsloth.ai/models/kimi-k2-thinking-how-to-run-l...).
But again, that’s for speed. You can run them more-or-less straight off the disk, but (~1TB / SSD_read_speed + computation_time_per_chunk_in_RAM) = a few minutes per ~word or punctuation.
Re: Claude Opus 4.5
#190Seeing 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…
I personally jumped ship from Claude to OpenAI due to the rate-limiting in Claude, and have no intention of coming back unless I get convinced that the new limits are at least double of what they were when I left.
Even if the code generated by Claude is slightly better, with GPT, I can send as many requests as I want and have no fear or running into any limit, so I feel free to experiment and screw up if necessary.