Meituan launches LongCat 2.0: 1.6T parameter MoE model with 1M+ context window at $0.30 per 1M input tokens
Meituan has released LongCat 2.0, a sparse mixture-of-experts language model with 48 billion active parameters out of 1.6 trillion total. The model features a 1,049,000 token context window and costs $0.30 per 1M input tokens and $1.20 per 1M output tokens.
LongCat 2.0 — Quick Specs
Meituan launches LongCat 2.0: 1.6T parameter MoE model with 1M+ context window
Meituan has released LongCat 2.0, a sparse mixture-of-experts (MoE) language model with 48 billion active parameters out of 1.6 trillion total parameters. The model is now available through OpenRouter's API.
Model specifications
LongCat 2.0 features a 1,049,000 token context window, placing it among the largest context windows available in production models. The sparse MoE architecture activates only 48 billion parameters per inference call while maintaining access to the full 1.6 trillion parameter base.
Pricing is set at $0.30 per 1 million input tokens and $1.20 per 1 million output tokens, making it competitively priced for long-context applications.
Target use cases
According to Meituan, LongCat 2.0 is designed for:
- Coding tasks and repository-level code changes
- Long-horizon problem solving
- Agentic workflows requiring extended context
The model operates as a text-to-text model and is accessed via the model ID meituan/longcat-2.0 on OpenRouter.
Technical architecture
The sparse MoE design allows LongCat 2.0 to maintain efficiency despite its massive total parameter count. By activating only 3% of its parameters (48B out of 1.6T) during inference, the model aims to balance computational cost with capability.
No benchmark scores have been publicly disclosed at this time. Training data cutoff date and additional technical details remain unannounced.
What this means
LongCat 2.0's million-token context window positions it for applications requiring extensive code repository analysis or long-document processing. The sparse MoE architecture suggests Meituan is following the industry trend of scaling total parameters while keeping active parameters manageable. At $0.30 per 1M input tokens, it's priced below several competitors offering similar context lengths, though real-world performance data will determine whether the pricing advantage translates to practical value. The model's availability through OpenRouter provides immediate API access without requiring direct integration with Meituan's infrastructure.
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