LongCat-Flash-Chat
Meituan開源權重MIT · 商用許可
描述
LongCat-Flash-Chat is Meituan's first open-source foundation model, a 560B parameter Mixture-of-Experts (MoE) model that dynamically activates 18.6B-31.3B parameters (~27B average) based on contextual demands. It features Zero-Computation Experts for efficient routing and supports 128K context. Optimized for conversational and agentic tasks, it shows competitive performance across reasoning, coding, instruction following, and domain benchmarks with particular strengths in tool use and complex multi-step interactions. Achieves over 100 tokens per second on H800 GPUs.
發布日期
2025-08-29
參數規模
560.0B
上下文長度
—
支援模態
text
能力雷達圖
70
general
60
coding
80
reasoning
60
science估算
70
agents
0
multimodal
缺少專門科學評測時,Science 由 LLM Stats 科學得分或推理能力估算。
排行榜排名
暫無排名資料
基準測試分數 (LLM Stats)
(LLM Stats (zeroeval))Chat
IFEvalGoogle Research (2023)
89.6%自報
Tau2 Airline
58.0%自報
Communication
Tau2 Telecom
73.7%自報
Tau2 Retail
71.3%自報
General
MMLU
89.7%自報
Language
CMMLU
84.3%自報
MMLU-Pro
82.7%自報
Math
MATH-500
96.4%自報
AIME 2025
61.3%自報
Reasoning
ZebraLogic
89.3%自報
HumanEvalOpenAI (2021)
88.4%自報
DROP
79.1%自報
GPQANYU + Cohere + Anthropic (2023)
73.2%自報
SWE-Bench Verified
60.4%自報
LiveCodeBench
48.0%自報
Terminal-Bench
39.5%自報
AA 評測指數
(Artificial Analysis)暫無 AA 評測資料
LLM Stats 分類評分
(LLM Stats (zeroeval))Instruction Following90
Language90
Legal90
Structured Output90
Finance90
Healthcare90
Math80
Chat70
Physics70
Reasoning70
General70
Biology70
Chemistry70
Communication70
Tool Calling70
Frontend Development60
Code60
Agents40
定價
暫無定價資料
速度
暫無速度資料
供應商價格排行
暫無提供商資料