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Comment by dannyw | Hacker News Reader

Haiku 5.5 is noticeably smarter than GPT-6 Luna, so I can see their pricing strategy here.

For a while Anthropic has lacked a cost effective “cheap” LLM for summarisation, compacting, RAG helpers, etc.

These ‘ephemeral’ workloads are often under 100k tokens, or can be structured to be under 100k.

In some coding benchmarks, Haiku 5.5 beats Sonnet 5! (Especially implementation; do a well defined Jira ticket; etc), it’s really impressive how much intelligence per dollar has grown in just a few short months.

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I said this in another comment, but Artificial Analysis has the cost per task of Haiku on max roughly equal to that of Sol on medium, and the latter is significantly more intelligent. (And I'd wager that Sol probably finishes tasks more quickly, even with Haiku inference being faster.) So Haiku really only makes sense on lower reasoning levels, and only if you care about intelligence and speed more than you do about cost effectiveness (where Luna currently dominates). And that's without even bringing Chinese models into the mix.

noticeably smarter remains to be seen in practice. For now, Haiku is a bit more expensive than Luna on < 100k token, but I just don't have any agentic work below 100k, so this is going to be 5x more expensive than shown on these charts. It's hardly competitive ...

No? Don't use these lower end models to work on small well defined tasks with a frontier model orchestrating? This approach works very well for me and don't have any issue staying under 100k. I have no idea if it's cheaper but it does seem to be much faster for tasks like QA.

> it’s really impressive how much intelligence per dollar has grown in just a few short months.

Open weights models giving a distant salute from afar

Yes, it was weird to see MiMo and DeepSeek missing in the article's comparison...

Is Mimo good? I've never tried it, but I've seen it mentioned three times in this subthread alone. DSv4.1 is my daily driver.

I have been settling on using Mimo 2.6 flash for discovery/research and glm 5.3 flash for implementation. So far I've been pretty happy with the results, but mimo can be quite slow. If speed is an issue, I just switch to glm 5.3 flash.

As context grows, it gets slower and dramatically slower. Otherwise it's pretty good.

And GLM 5.3 Flash.

I haven't really tried it that much. I use GLM 5.3 a lot, especially with Coralbricks where the cache reads are free so I can let it think a lot without breaking the bank in the following turns. It's really good for bughunt, planning, and security work.

Maybe I should try the flash...

It's not that weird. Most companies considering paying Anthropic are probably not considering Chinese models as alternatives. Many don't even realize they exist.

The thing is: availability of near-SOTA cheap Chinese models is forcing OAI and Anthropic to bring prices down and offer more efficient models, instead of simply focusing on super expensive SOTA LLMs.

Is it? I would guess that it's much more about the race to get customers as they both near IPO than anything to do with the Chinese models.

we are actively preparing to move our devs from closed to open models, take it as a piece of anecdata

the trend in industry is clear by now though

Yes. We did the same a few weeks ago. Everybody I talk with in the EU startup ecosystem is either doing the same or considering doing it.

one only has to look at the providers like OpenRouter and OpenCode to see the massive swing since this summer ... or the fear mongering by Big Ai about open weights since

Not surprised by EU heading that way with how we here in 'murica are treating the rest of the world

at this point, there is no meaningful difference in day-to-day work

> one only has to look at the providers like OpenRouter and OpenCode to see the massive swing since this summer

Doesn't this have more to do with LLMs getting more usage overall? I don't see how that's a sign that people are leaving OpenAI/Anthropic.

"companies" is a meaningless metric.

If you want to make it about 99% of real world companies, they are all on Gemini or Copilot anyway, nobody is going through legal and procurement to get models from dubious silicon valley startups when you have relations with Microsoft or Google or Amazon from ages because some benchmark is showing some minor digit benefit when vibe coding GTA 6.

I said "most companies considering paying Anthropic", which is not the same as "most companies". I also don't agree that "nobody" is doing this; I have lots of anecdata suggesting otherwise. Maybe the majority of companies are using the easy option of Copilot or Gemini like you said, but it's nowhere near 99%.

Yes it is. Literally every company Ive spoken too about this only has MS teams co-pilot lol. Like all of them are using the most basic form of AI.

They dont even know about Anthropic and think its just "AI". By the way this includes one of the largest power systems design firms in the world, who helps build many datacenters... Uses only MS copilot.

Do you understand how many companies there are? Your anecdata is wholly useless

Well, I can add two more points to your anecdata. I personally know of two companies where only exposure for peasants is Copilot.

Yep, this doesn’t surprise me.

Umm, just go look up the whole of software revenues globally and compare that to OpenAI. Its very small. Nobody is paying for SOTA models outside software engineering and ancillaries, except for some outliers fields like consulting. Then there's techies in every field who use it, but not companies themselves.

Companies as a whole, do not care about this technology, except tech companies and its adoption cant even be compared to CRMs. A company might buy a SaaS product with AI but most of them are not purchasing Anthropic subscriptions lol.

Vibe coding gta 6 haha

The benchmarks are very long form logic, knowledge, and coding tasks though. I'm very interested in Haiku 5.5's performance on ObviousBench where Luna 6 is currently SotA.

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