Anthropic's Claude Haiku 5.5 slashes costs by 75% while tripling benchmark scores
Anthropic has launched Claude Haiku 5.5, its fastest and cheapest small model yet, designed for high-volume tasks like summarization, classification, and live support. It costs around 75% less to run than Haiku 4.5 and delivers massive performance gains, including a jump from 15.7% to 72.4% on OSWorld 2.1. The model also introduces an adjustable effort setting and pairs well with Opus 5.5 and Sonnet 5.5 as a coding subagent.
We're very impressed with Claude Haiku 5.5, particularly its speed. We ran it through our eval suite for AI Teammates, our AI agent product, covering use cases like triaging bugs, setting up projects, and searching large portfolios to surface high-risk or overdue work. Compared with the model we use today, we saw over a 30% reduction in latency for task completions and up to 2.5x faster inference per agent turn. It's a noticeably snappier experience.
- simonw
Pelicans riding bicycles for Haiku at the different thinking levels: https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
Low messes up the bicycle frame, but medium/high/xhigh/max all get the bicycle frame right.
The max one took 5 minutes 9 seconds and cost 3.3826 cents. The cheapest one (low) cost 0.0936 cents and took 7 seconds.
The most recent release of my llm-anthropic plugin queries the Anthropic model listing API directly, so I didn't have to upgrade the plugin to add support for this model:
llm install llm-anthropic -U
llm anthropic refresh
llm -m claude-haiku-5.5 'prompt goes here'
EDIT: Here's the Haiku 4.5 pelican from a year ago for comparison, it was terrible: https://simonwillison.net/2025/Oct/15/claude-haiku-45/
- minimaxir
Pricing is...a bit weird.
Input
$0.10 / MTok for prompts up to 100,000 tokens
$0.50 / MTok for prompts over 100,000 tokens
Output
$0.50 / MTok for prompts up to 100,000 tokens
$2.50 / MTok for prompts over 100,000 tokens
100k tokens is an absurdly low cutoff and it is only applicable to Haiku and not Sonnet or Opus. It's a low enough cutoff that it will be quickly exceeded if you are doing anything with Agents; for typical generation or Jev-like classifiers, it's a good value and as noted in this article, that is apparently the vast majority of Haiku use.
In both cases, still much cheaper than Haiku 4.5's $1 input / $5 output and these prices better compete with GPT-6 Luna. ($0.10 input / $0.50 output, but with no token threshold [EDIT: the threshold for Luna is apparently 272k])
- charlesabarnes
> Second, this week, we’ll roll out a new monthly API credit to all Max and Team subscribers for use on the Claude Platform. Max 5x users will get $100 in credits per month, Max 20x users will get $200, and Team subscribers will receive up to $500, pooled across their users
This is a very big benefit for me. I can now ship actual ai enhanced features behind my subscription without paying extra or fully relying on on-device models. I do worry that this is to soften the blow for user-unfriendly changes
- chriddyp
Ran our DataAnalyticsBench benchmark on it: https://plotly.com/blog/claude-haiku-5-5-plotly-data-analyti...
9x cheaper than Haiku 4.5 and 2 letter grades better. It's also now the fastest model (using the default speeds, not trying any of the other models "Fast" mode) to complete the exam.
Similar ballpark to Luna in price, cost, and accuracy. These are very cheap models: $0.38 to answer 40 in-depth data analytics questions (compared to $15 for Opus 5.5 or $20 for Astra).
Overall very good at data analysis - handling all of the straightforward data analytics questions correctly. It fell short answering some of the questions that required some deeper statistical analysis like looking into other variables. In other words, it's not as persistent as other models in its analysis, which I think we'd expect from how they're positioning the model.
Compared to OpenAI: GPT-6 Luna did a bit better and was about 30% the cost of Haiku 5.5. GPT-6.1 Sol got all answers correct, but was 10x more expensive.
- simonw
My complaint about Haiku 4.5 was that it was 10x the price of GPT-6 Luna.
> Claude Haiku 5.5 is priced 90% lower than Claude Haiku 4.5 for requests up to 100,000 tokens, and 50% lower for requests over 100,000 tokens
Haiku and Luna now have the exact same price up to 100,000 tokens. Luna is now cheaper for anything after 100,000 tokens, even after Luna's own price increases at 270,000 it's still less than Haiku.
So it sounds like they've directly addressed that problem. Their self-reported benchmarks are all higher than Luna too.
- jjcm
Ran image -> html tests for this. I was curious if this smaller model was good enough for complex UI. It was not.
Haiku 5.5: https://html.non.io/lcars-haiku-5.5/
Opus 5.5 for comparison: https://html.non.io/lcars-opus-5.5
Designs it was building from: https://diffui.ai/app/canvas/5093e689-1e74-4f26-b632-2a4500f...
One interesting thing is it took a look at the job at hand, and immediately delegated it to Opus 5.5. It at least knows what it isn't good at. Very fast though, and likely best used for small subagent tasks / tightly scoped work.
- seaal
The monthly API credits for Max plan seems fantastic, especially considering Haiku pricing. Being able to actually use my Claude plan for other harnesses and use-cases on top of regular CC usage is everything I wanted.
Anthropic has really been doing all the right things in the past few weeks, while OpenAI continues to fumble the bag.
- wyrdcurt
About time Anthropic released a competitive cheap model. Haiku 4.5 has been too expensive compared to its performance for months now (in fact I don't remember being too impressed even when it was released). This one actually looks worth using in some scenarios. If it's really as much of a step up from Luna as the benchmarks they've shown indicate, it'll probably replace Luna in my workflows. 100k tokens is a pretty low threshold before the price goes up, but I tend to use these smaller models for smaller tasks anyway.
- bouk
This is great! Been using GPT 6 Luna for decompiling my childhood favorite game (Age of Mythology) and this means I can throw Haiku into the mix as well. 17352/21965 functions matched so far...
- d1l
At work we use haiku 4.5 for a handful of latency sensitive tasks that are fairly simple. It performs well. Just started testing 5.5 as I’ve been anticipating a nice improvement since it was teased. Results so far are trash. Prompt leakage even. And it’s slower. I guess it’s cheap but I think they got the balance wrong on this.