Forward Future Tools Library
LongCat Flash
LongCat Flash delivers a fast, open-source 560B MoE language model for developers and businesses building conversational applications and tool-using agents.
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›What is LongCat Flash?
LongCat Flash is Meituan's open-source 560B-parameter language model, using a Mixture-of-Experts architecture that activates 18.6B to 31.3B parameters per token. It is designed for fast inference, tool use, multi-step reasoning, and interaction with complex environments. The model is available through Hugging Face and GitHub.
›What are the pros and cons of LongCat Flash?
Strengths
The model activates a smaller subset of its 560B parameters for each token
Inference is reported at more than 100 tokens per second
Supports tool use, multi-step reasoning, and agentic workflows
Available for research and commercial use through open-source distribution
The website reports output inference costs as low as $0.7 per million tokens
Trade-offs
The released model is described as a non-thinking foundation model, which may limit workflows that require a dedicated thinking mode
The official API is not currently routed through the LLM Stats gateway
The model's licensing is presented inconsistently across sources, with the website citing Apache 2.0 and GitHub listing MIT
›What are LongCat Flash’s key features?
560B total parameters with 18.6B to 31.3B dynamically activated per token
Mixture-of-Experts architecture with shortcut-connected computation
Inference speeds above 100 tokens per second
Tool use and multi-step reasoning for agentic tasks
Support for complex environment interaction
Open-source distribution through Hugging Face and GitHub
›What are the best use cases for LongCat Flash?
Build conversational applications that need low first-token latency and real-time responses
Create agents that call tools and complete multi-step tasks
Develop applications involving complex reasoning and environment interaction
Research and test large open-source language models using the Hugging Face or GitHub releases
›Who is LongCat Flash best for?
developersA strong fit for developers building fast conversational applications or agents with tool-use requirements.
small teamSmall teams can use the open-source release to test and deploy an agentic language model without relying only on a proprietary model.
enterpriseEnterprises may value the reported inference speed and token economics for applications requiring frequent model responses.
AI researchersResearchers get access to a large MoE model with dynamic parameter activation and published agentic benchmark results.
Not for
- Teams specifically looking for a model with a separate thinking or extended-deliberation mode should consider another option.
- Buyers seeking a clearly documented, tiered hosted API price should verify the provider's current commercial terms before adoption.
›What are the best LongCat Flash alternatives?
Together AIChoose this instead if you want a hosted AI acceleration cloud for model inference and training rather than managing an open-source model deployment.→
Google GeminiChoose this instead if you want a proprietary model positioned for broad multitasking and content-generation workflows.→
Claude.aiChoose this instead if you prefer a managed conversational AI product rather than an open-source model release.→
DeepResearch→