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LongCat-Flash-Chat

MeituanOpen WeightMIT · Commercial OK

Description

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.

Release Date
2025-08-29
Parameters
560.0B
Context Length
Modalities
text

Capability Radar

70
general
60
coding
80
reasoning
60
scienceest.
70
agents
0
multimodal

Science is estimated from LLM Stats science scores or reasoning when no dedicated science benchmarks are available.

Rankings

Domain#RankScoreSource
Agentic Capability30
55.0
LS

Benchmark Scores (LLM Stats)

(LLM Stats (zeroeval))

Agents

Terminal-Bench39.5%SR

Biology

GPQANYU + Cohere + Anthropic (2023)73.2%SR

Code

HumanEvalOpenAI (2021)88.4%SR
SWE-Bench Verified60.4%SR
LiveCodeBench48.0%SR

Communication

Tau2 Telecom73.7%SR
Tau2 Retail71.3%SR
Tau2 Airline58.0%SR

Finance

MMLU89.7%SR
MMLU-Pro82.7%SR

General

IFEvalGoogle Research (2023)89.6%SR
CMMLU84.3%SR

Math

MATH-50096.4%SR
DROP79.1%SR
AIME 202561.3%SR

Reasoning

ZebraLogic89.3%SR

AA Evaluation Indices

(Artificial Analysis)

No AA evaluation data available

LLM Stats Category Scores

(LLM Stats (zeroeval))
Legal
90
Structured Output
90
Instruction Following
90
Language
90
Finance
90
Healthcare
90
Math
80
Physics
70
Reasoning
70
General
70
Biology
70
Chemistry
70
Communication
70
Tool Calling
70
Frontend Development
60
Code
60
Agents
40

Pricing

No pricing data available

Speed

No speed data available

Provider Price Ranking

No provider data available

External Sources