longcat · Open weights
LongCat 2.0
Meituan's LongCat 2.0 is an open-weight agentic model for coding, tool use, and long-context workflow automation, with reasoning disabled for faster direct answers.
- Tools
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.75
- Output
- $3.00
- Cache read
- $0.015
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 131.1K
- Average output (7 days)
- 368 tokens
- Longer than 38% of 468 models
Side by side
Compare models
Put LongCat 2.0 next to up to three other models. The comparison stays in the link, so you can share it.
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
Intelligence Index
19.1
Better than 48% of 326 scored models
Indexes
Coding Index
45.3Composite of the coding evaluations
Better than 38% of 168 scored models
Agentic work
AutomationBench-AA
4.5%Workflow automation, penalized for guardrail violations
Better than 24% of 173 scored models
AutomationBench-AA tasks completed
0.5%Workflows finished end to end without a guardrail violation
Better than 24% of 173 scored models
AA-Briefcasev1.1
739 EloAgentic knowledge work, rated head to head
Better than 26% of 166 scored models
GDPval-AAv2.1
869 EloEconomically valuable occupational tasks, rated head to head
Better than 29% of 187 scored models
Document reasoning
GDP.pdf
6.4%Professional reasoning over PDF documents, all-pass rate
Better than 29% of 171 scored models
AA-LCRv1.1
65.0%Reasoning across long documents
Better than 40% of 309 scored models
Reasoning and knowledge
Humanity’s Last Exam
33.7%Expert-level questions across academic fields
Better than 67% of 323 scored models
GPQA Diamond
78.0%Graduate-level science questions
Better than 41% of 291 scored models
Coding
Terminal-Benchv4.0
0.0%Practical software engineering in a terminal
Better than 0% of 171 scored models
SciCode
36.3%Scientific computing in Python
Better than 16% of 174 scored models
Legacy evaluations
AA-LCR (unversioned)
65.0%Long-context reasoning, earlier grading
Better than 40% of 309 scored models
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Prompt cache hits
- 0.0%
- About $0.75 per 1M input tokens with caching
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "longcat-2.0",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="longcat-2.0",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)longcat
Related models
Other longcat models, starting with the same family.