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longcat · Open weights

LongCat 2.0 Thinking

Added Jul 21, 2026Open weights

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Use in the app

Meituan's LongCat 2.0 Thinking is the reasoning-enabled variant for harder coding, tool use, multi-step reasoning, and long-context agent workflows.

  • Reasoning
  • 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)
1.1K tokens
Longer than 73% of 468 models

Side by side

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TryDeepSeek V4 Flash 0423GLM 4.6 Turbo (Thinking)Qwen3.6 27B TEEAll 3

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

3.8Catalog models by score55.1

Indexes

  • Coding Index

    45.3

    Composite 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 Elo

    Agentic knowledge work, rated head to head

    Better than 26% of 166 scored models

  • GDPval-AAv2.1

    869 Elo

    Economically 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.

Throughput
56.1 tok/s
Faster than 38% of 254 models
Time to first token
4.0 s
Quicker than 45% of 254 models
Prompt cache hits
16.9%
About $0.63 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.

Hourly request success · last 72 hoursLowest hour 100.0%
  • 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.

Read the quickstart
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:thinking",
    "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:thinking",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

longcat

Other longcat models, starting with the same family.