Was anyone else slightly disappointed that this new product doesn't respond in Haiku, as the name would imply?
It's not a new product; just a new version.
Claude Haiku 4.5
21–30 of 292 posts
Re: Claude Haiku 4.5
#22What is the use case for these tiny models? Is it speed? Is it to move on device somewhere? Or is it to provide some relief in pricing somewhere in the API? It seems like most use is through the Claude subscription and therefore the use case here is basically non-existent.
for me its the speed; eg cerebras qwen coder gets you a completely different workflow as its practically instant (3k tps) -- feels less like an agent and more like a natural language shell, very helpful for iterating on a plan that you them forward to a bigger model
Re: Claude Haiku 4.5
#23$1/M input tokens and $5/M output tokens is good compared to Claude Sonnet 4.5 but nowadays thanks to the pace of the industry developing smaller/faster LLMs for agentic coding, you can get comparable models priced for much lower which matters at the scale needed for agentic coding. Given that Sonnet is still a popular model for coding despite the much higher cost, I expect Haiku will get traction if the quality is a…
With caching that's 10 cents per million in. Most of the cheap open source models (which this claims to beat, except glm 4.6) have limited and not as effective caching. This could be massive.
The funny thing is that even in this area Anthropic is behind other 3 labs (Google, OpenAI, xAI). It's the only one out of those 4 that requires you to manually set cache breakpoints, and the initial cache costs 25% more than usual context. The other 3 have fully free implicit caching. Although Google also offers paid, explicit caching.
https://docs.claude.com/en/docs/build-with-claude/prompt-cac...
https://ai.google.dev/gemini-api/docs/caching
Re: Claude Haiku 4.5
#24Pretty cute pelican on a slightly dodgy bicycle: https://tools.simonwillison.net/svg-render#%3Csvg%20viewBox%...
imagine finding the full text of the svg in the library of babel. Great work!
Re: Claude Haiku 4.5
#25Earlier quoted context omitted.
With caching that's 10 cents per million in. Most of the cheap open source models (which this claims to beat, except glm 4.6) have limited and not as effective caching. This could be massive.
$1/M is hardly a big improvement over GPT5's $1.250/M (or Gemini Pro's $1.5/M), and given how much worse Haiku is than those at any kind of difficult problem (or problems with a large context size), I can't imagine it being a particularly competitive alternative for coding. Especially for anything math/logic related, I find GPT5 and Gemini Pro to be significantly better even than Opus (which reflects in their models…
GPT-5 is $10/M for output tokens, twice the cost of Haiku 4.5 at $5/M, despite Haiku apparently being better at some tasks (SWE Bench).
I suppose it depends on how you are using it, but for coding isn't output cost more relevant than input - requirements in, code out ?
Re: Claude Haiku 4.5
#26Earlier quoted context omitted.
With caching that's 10 cents per million in. Most of the cheap open source models (which this claims to beat, except glm 4.6) have limited and not as effective caching. This could be massive.
The funny thing is that even in this area Anthropic is behind other 3 labs (Google, OpenAI, xAI). It's the only one out of those 4 that requires you to manually set cache breakpoints, and the initial cache costs 25% more than usual context. The other 3 have fully free implicit caching. Although Google also offers paid, explicit caching. https://docs.claude.com/en/docs/build-with-claude/prompt-cac... https://ai.google…
I vastly prefer the manual caching. There are several aspects of automatic caching that are suboptimal, with only moderately less developer burden. I don’t use Anthropic much but I wish the others had manual cache options
Re: Claude Haiku 4.5
#27Earlier quoted context omitted.
The funny thing is that even in this area Anthropic is behind other 3 labs (Google, OpenAI, xAI). It's the only one out of those 4 that requires you to manually set cache breakpoints, and the initial cache costs 25% more than usual context. The other 3 have fully free implicit caching. Although Google also offers paid, explicit caching. https://docs.claude.com/en/docs/build-with-claude/prompt-cac... https://ai.google…
I vastly prefer the manual caching. There are several aspects of automatic caching that are suboptimal, with only moderately less developer burden. I don’t use Anthropic much but I wish the others had manual cache options
What's sub-optimal about the OpenAI approach, where you get 90% discount on tokens that you've previously sent within X minutes?
Re: Claude Haiku 4.5
#28Was anyone else slightly disappointed that this new product doesn't respond in Haiku, as the name would imply?
If you want to see it generate a Haiku from your webcam I just upgraded my silly little bring-your-own-key Haiku app to use the new model: https://tools.simonwillison.net/haiku
Re: Claude Haiku 4.5
#29The main thing holding these Anthropic models back is context size. Yes, quality deteriorates over a large context window, but for some applications, that is fine. My company is using grok4-fast, the Gemini family, and GPT4.1 exclusively at this point for a lot of operations just due to the huge 1m+ context.
Re: Claude Haiku 4.5
#30Very preliminary testing is very promising, seems far more precise in code changes over GPT-5 models in not ingesting irrelevant to the task at hand code sections for changes which tends to make GPT-5 as a coding assistant take longer than sometimes expected. With that being the case, it is possible that in actual day-to-day use, Haiku 4.5 may be less expensive than the raw cost breakdown may appear initially, though the increase is significant.
Branding is the true issue that Anthropic has though. Haiku 4.5 may (not saying it is, far to early to tell) be roughly equivalent in code output quality compared to Sonnet 4, which would serve a lot users amazingly well, but by virtue of the connotations smaller models have, alongside recent performance degradations making users more suspicious than beforehand, getting these do adopt Haiku 4.5 over Sonnet 4.5 even will be challenging. I'd love to know whether Haiku 3, 3.5 and 4.5 are roughly in the same ballpark in terms of parameters and course, nerdy old me would like that to be public information for all models, but in fairness to companies, many would just go for the largest model thinking it serves all use cases best. GPT-5 to me is still most impressive because of its pricing relative to performance and Haiku may end up similar, though with far less adoption. Everyone believes their task requires no less than Opus it seems after all.
For reference:
Haiku 3: I $0.25/M, O $1.25/M
Haiku 4.5: I $1.00/M, O $5.00/M
GPT-5: I $1.25/M, O $10.00/M
GPT-5-mini: I $0.25/M, O $2.00/M
GPT-5-nano: I $0.05/M, O $0.40/M
GLM-4.6: I $0.60/M, O $2.20/M