Does anyone with more insight into the AI/LLM industry happen to know if the cost to run them in normal user-workflows is falling? The reason I'm asking is because "agent teams" while a cool concept, it largely constrained by the economics of running multiple LLM agents (i.e. plans/API calls that make this practical at scale are expensive).
A year or more ago, I read that both Anthropic and OpenAI were losing money on every single request even for their paid subscribers, and I don't know if that has changed with more efficient hardware/software improvements/caching.
Will Opus 4.6 via Claude Code be able to access the 1M context limit? The cost increase by going above 200k tokens is 2x input, 1.5x output, which is likely worth it especially for people with the $100/$200 plans.
I found that "Agentic Search" is generally useless in most LLMs since sites with useful data tend to block AI models.
The answer to "when is it cheaper to buy two singles rather than one return between Cambridge to London?" is available in sites such as BRFares, but no LLM can scrape it so it just makes up a generic useless answer.
My guess is that this is going to be the future for LLMs too. It will get harder or more expensive for AI companies to train their models on the latest information as most sites will block the scrapers or ask for a fee.
There might be a future where you’ll have to pay more for an up to date model vs a legacy (out of date) model
I love Claude but use the free version so would love a Sonnet & Haiku update :)
I mainly use Haiku to save on tokens...
Also dont use CC but I use the chatbot site or app... Claude is just much better than GPT even in conversations. Straight to the point. No cringe emoji lists.
When Claude runs out I switch to Mistral Le Chat, also just the site or app. Or duck.ai has Haiku 3.5 in Free version.
> Long-running conversations and agentic tasks often hit the context window. Context compaction automatically summarizes and replaces older context when the conversation approaches a configurable threshold, letting Claude perform longer tasks without hitting limits.
Not having to hand roll this would be incredible. One of the best Claude code features tbh.
From the press release at least it sounds more expensive than Opus 4.5 (more tokens per request and fees for going over 200k context).
It also seems misleading to have charts that compare to Sonnet 4.5 and not Opus 4.5 (Edit: It's because Opus 4.5 doesn't have a 1M context window).
It's also interesting they list compaction as a capability of the model. I wonder if this means they have RL trained this compaction as opposed to just being a general summarization and then restarting the agent loop.
The benchmarks are cool and all but 1M context on an Opus-class model is the real headline here imo. Has anyone actually pushed it to the limit yet? Long context has historically been one of those "works great in the demo" situations.
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[ 3.3 ms ] story [ 80.4 ms ] threadCurious how long it typically takes for a new model to become available in Cursor?
well that explains quite a bit
A year or more ago, I read that both Anthropic and OpenAI were losing money on every single request even for their paid subscribers, and I don't know if that has changed with more efficient hardware/software improvements/caching.
The answer to "when is it cheaper to buy two singles rather than one return between Cambridge to London?" is available in sites such as BRFares, but no LLM can scrape it so it just makes up a generic useless answer.
There might be a future where you’ll have to pay more for an up to date model vs a legacy (out of date) model
I mainly use Haiku to save on tokens...
Also dont use CC but I use the chatbot site or app... Claude is just much better than GPT even in conversations. Straight to the point. No cringe emoji lists.
When Claude runs out I switch to Mistral Le Chat, also just the site or app. Or duck.ai has Haiku 3.5 in Free version.
> Long-running conversations and agentic tasks often hit the context window. Context compaction automatically summarizes and replaces older context when the conversation approaches a configurable threshold, letting Claude perform longer tasks without hitting limits.
Not having to hand roll this would be incredible. One of the best Claude code features tbh.
It also seems misleading to have charts that compare to Sonnet 4.5 and not Opus 4.5 (Edit: It's because Opus 4.5 doesn't have a 1M context window).
It's also interesting they list compaction as a capability of the model. I wonder if this means they have RL trained this compaction as opposed to just being a general summarization and then restarting the agent loop.
Claude figured out zig’s ArrayList and io changes a couple weeks ago.
It felt like it got better then very dumb again the last few days.