1.6T MoE model for long-horizon agentic coding
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Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free plan available, paid tiers above
Biggest pro
Open weights under a permissive MIT license, free to download, fine-tune, and self-host
Biggest con
Running a 1.6T model locally is impractical without serious GPU or accelerator infrastructure
TL;DR - LongCat-2.0
- Open-weights agentic coding model from Meituan, released under a permissive MIT license.
- 1.6-trillion-parameter Mixture-of-Experts design, about 48 billion active parameters per token, with a 1-million-token context.
- Led OpenRouter usage for roughly two months as the stealth model 'Owl Alpha' before going public.
Pricing: Free plan available
Best for: Growing teams
What is LongCat-2.0?
LongCat-2.0 is an open-weights large language model from Meituan, built for long-horizon agentic coding. It uses a 1.6-trillion-parameter Mixture-of-Experts design that activates roughly 48 billion parameters per token, paired with a 1-million-token context window, and ships under a permissive MIT license. Before its public release it spent about two months topping OpenRouter usage charts as the stealth model 'Owl Alpha'. It is also notable for being trained entirely on domestic Chinese chips, and its API processes context-cache hits free of charge.
Pros & Cons
Pros
- Open weights under a permissive MIT license, free to download, fine-tune, and self-host
- Frontier-scale 1.6T Mixture-of-Experts with a 1-million-token context for large codebases and long agent runs
- Proven real-world usage, having led OpenRouter charts as 'Owl Alpha'
- Strong focus on autonomous, long-horizon coding and engineering tasks
- API makes context-cache hits free, lowering cost on repetitive long-context work
Cons
- Running a 1.6T model locally is impractical without serious GPU or accelerator infrastructure
- The hosted API routes data through a China-based provider, a compliance consideration for some teams
- Newer model with a smaller tooling and fine-tune ecosystem than established models
Key Features
Natural language code generationAutomated debugging and error fixingCode refactoring and optimizationMulti-language and framework supportSeamless IDE and workflow integration
Pricing
Freemium
LongCat-2.0 offers a generous free tier with optional paid upgrades for advanced features.
Reviews
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LongCat-2.0 FAQ
How does LongCat-2.0 handle long-horizon agentic coding tasks?
LongCat-2.0 is designed for long-horizon agentic coding with a 1.6-trillion-parameter Mixture-of-Experts architecture that activates roughly 48 billion parameters per token, paired with a 1-million-token context window. This allows it to maintain coherence and execute complex, multi-step coding workflows across large codebases without losing track of earlier context.
How does LongCat-2.0 compare to Claude Code for agentic coding?
Unlike Claude Code, which is a proprietary tool from Anthropic, LongCat-2.0 is an open-weights model released under a permissive MIT license, meaning you can download, fine-tune, and self-host it freely. LongCat-2.0 also offers a 1-million-token context window and uses a 1.6-trillion-parameter Mixture-of-Experts design, whereas Claude Code's underlying model has a smaller context window and is not open-weight.
What are the main limitations or trade-offs of using LongCat-2.0?
Running LongCat-2.0 locally is impractical without serious GPU or accelerator infrastructure due to its 1.6-trillion-parameter size. Additionally, its hosted API routes data through a China-based provider, which may be a compliance consideration for some teams, and it has a smaller tooling and fine-tune ecosystem compared to more established models.
Which teams benefit most from using LongCat-2.0?
Teams that need to work on large codebases and run long, autonomous agentic coding sessions benefit most from LongCat-2.0, thanks to its 1-million-token context window and Mixture-of-Experts design. It is also ideal for organizations that require open-weight models for self-hosting, fine-tuning, or avoiding vendor lock-in, given its permissive MIT license.
How is LongCat-2.0 priced?
LongCat-2.0 is available on a free tier, with paid plans for more usage and features. Its API also processes context-cache hits free of charge, which lowers costs for repetitive long-context work.
Can LongCat-2.0 be self-hosted and fine-tuned?
Yes, LongCat-2.0 is released under a permissive MIT license, so you can download, fine-tune, and self-host it freely. However, self-hosting requires serious GPU or accelerator infrastructure because the model has 1.6 trillion total parameters.
Does LongCat-2.0 offer any cost-saving features for repeated use on the same codebase?
Yes, LongCat-2.0's API makes context-cache hits free of charge, which significantly reduces costs when you repeatedly process the same long-context codebase. This is especially valuable for teams running frequent agentic coding sessions on large projects.
Why did LongCat-2.0 gain attention on OpenRouter before its official release?
LongCat-2.0 spent about two months topping OpenRouter usage charts as the stealth model 'Owl Alpha', demonstrating its real-world performance and popularity for agentic coding tasks. This proven usage indicates strong capability for long-horizon coding workflows.
Source: longcat.ai