{
  "id": 19919264,
  "title": "LongCat-2.5 Open Weights vs Kimi K3.1 Pro: MIT Wins",
  "url": "https://urgent.news/2026/11/14/longcat-2-5-open-weights-vs-kimi-k3-1-pro-mit-wins",
  "topic": "culture",
  "section": "Culture",
  "published": "2026-11-14T04:44:16.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/shaam_ai/longcat-25-open-weights-vs-kimi-k31-pro-mit-wins-2nof"
  },
  "original_language": "en",
  "account": "Meituan released the weights for its LongCat-2.5 open weights model on Hugging Face with an MIT license on November 10, 2026. This makes it the lowest-risk large open-weights base to build on this month, as it has no revenue gates or territory carve-outs. The model is 1.6 trillion parameters with about 48 billion parameters active per token, and it comes in a 3.56 TB repository. For most Indian developers, it's recommended to rent the hosted API first at roughly ₹28 per million input tokens, and only self-host if already operating trillion-parameter MoE serving. The MIT license grants no rights to Meituan trademarks or patents, which is important for legal review. Benchmarks show that LongCat-2.5 is close to the leaders in Terminal Bench v2.1, but not ahead. The model adds native visual input alongside agentic coding, and benchmarks are mostly in-house. The MIT license is more permissive than the licenses of Kimi K3.1 Pro and ERNIE 5.5 Flash Base, both of which have additional constraints. To download the LongCat-2.5 open weights, you can use the command \"hf download hf://meituan-longcat/LongCat-2.5\". The model can be run on NPU platforms through SGLang-FluentLLM, but GPU users should wait for community support. Renting the API is recommended for better cost-effectiveness, especially for prototype, evaluation, and spiky traffic.",
  "summary": "On 10 November 2026 Meituan published the LongCat-2.5 open weights on Hugging Face under the MIT licence: a 1.6 trillion parameter mixture-of-experts model with about 48 billion parameters active per token, in a 3.56 TB repository. On licence terms it beats Kimi K3.1 Pro and Baidu's ERNIE 5.5 Flash Base, because neither revenue gates nor territory carve-outs apply. For most Indian developers and…",
  "key_points": [
    "Meituan released LongCat-2.5 model weights on Hugging Face under MIT license on November 10, 2026.",
    "Model has 1.6 trillion parameters with 48 billion active per token, repository size 3.56 TB."
  ],
  "editors_take": "Meituan's permissive licensing removes the legal and commercial hurdles found in competing models, offering developers a low-risk foundation for building large-scale applications without territory or revenue restrictions.",
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}