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LongCat-2.5: Native Multimodality for Agentic Tasks

longcat.ai85 points25 comments
Screenshot of LongCat-2.5: Native Multimodality for Agentic Tasks

LongCat 2.5 is presented as a multimodal model for agentic tasks, and commenters focused on how its benchmarks compare with frontier systems. One commenter objected that comparisons to older GPT and Claude models, published without a price comparison, could make the results look more favorable than they are. Others argued that named benchmarks offer a useful measure of capability, and that the preview date made those particular comparisons relevant. Another commenter said LongCat’s pricing matches DeepSeek’s and its benchmark results look comparable, with cache-hit rate and speed left as practical differentiators. A commenter also saw the comparisons as showing how open or locally accessible models can approach the level of frontier models from a few months earlier.

Other reactions centered on whether the release was ready to use. One commenter found the GitHub and Hugging Face links unclear about access to weights, described a chat link redirecting to a broken login page, and reported unhelpful Chinese-language responses. They took these problems, along with weak basic answers, as signs of a rushed, benchmark-focused release. The exchange also touched on rising expectations: capabilities once considered remarkable for open-weight models have quickly become a baseline for some users. One commenter cautioned that LongCat’s 1.6-trillion-parameter size makes running it at home unrealistic, while another valued the prospect of using a model without relying on Anthropic or OpenAI.

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