LongCat-2.5
Description
LongCat-2.5 is Meituan's native multimodal Mixture-of-Experts model for long-horizon agentic tasks, with about 1.6T total parameters and roughly 48B activated per token. It builds on LongCat-2.0 with stronger native visual understanding and agentic coding, representing images as multi-level discrete tokens (RVQ over native-resolution features) so the backbone processes visual and text inputs in one token format. Training adds more long-horizon trajectories, large-scale asynchronous agentic RL across mixed harnesses, and multi-teacher on-policy distillation. Meituan also reports optimizing long-context training and W4A4 inference for domestic AI accelerators. The LongCat API (OpenAI, OpenAI Responses and Anthropic compatible) exposes it as LongCat-2.5 with a 1M-token context window; Meituan's Quick Start and FAQ list a 128K maximum output, while the Model Parameters page allows max_tokens up to 262,144. Launch pricing is a limited-time discount of $0.30 / $1.20 per MTok (cached input $0.006). Weights were not public at announcement.
Capability Radar
Science is estimated from LLM Stats science scores or reasoning when no dedicated science benchmarks are available.
Rankings
| Domain | #Rank | Score | Source |
|---|---|---|---|
| Agentic Capability | 106 | 40.0 | LS |
| Multimodal Ranking | 71 | 53.0 | LS |
Benchmark Scores (LLM Stats)
(LLM Stats (zeroeval))Agents
Code
Finance
General
Math
Multimodal
Reasoning
AA Evaluation Indices
(Artificial Analysis)No AA evaluation data available
LLM Stats Category Scores
(LLM Stats (zeroeval))Pricing
Speed
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Provider Price Ranking
Provider Price Ranking
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