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LongCat-2.0 Explained: The Meme-Cat Model That Secretly Topped OpenRouter as Owl Alpha

2026-07-03
Consensus Google Gemini Google Gemini
Models consulted
  • OpenAI GPT-5.5
  • Mistral Mistral Medium 3.5
  • Anthropic Claude Claude Opus 4.8
  • Google Gemini Gemini 3.5 Flash
  • DeepSeek DeepSeek V4 Pro
  • Grok Grok 4.20

Consensus answer

LongCat-2.0 Explained: The "Meme-Cat" Model That Secretly Topped OpenRouter as Owl Alpha

LongCat-2.0 is Meituan’s open-source large language model designed specifically for agentic coding. Rather than simply writing isolated code snippets, this model is built to operate within developer tools, reason through multi-step tasks, inspect files, run terminal commands, debug errors, and maintain coherence across massive codebases.

Before its official announcement on June 30, 2026, Meituan quietly deployed a preview version of the model on OpenRouter under the anonymous alias “Owl Alpha.” This stealth model quickly gained massive traction among agent developers before its true identity was revealed. According to Meituan, the preview ranked among the top three models globally by call volume on OpenRouter, with reports indicating it was highly favored in agentic tools like Hermes Agent, Claude Code, and OpenClaw.


What is LongCat-2.0?

LongCat-2.0 is a 1.6-trillion-parameter Mixture-of-Experts (MoE) model. While 1.6 trillion is an enormous figure, its MoE architecture means it does not activate all parameters for every token. Instead, it dynamically routes each token through specialized expert networks, activating roughly 33B to 56B parameters per token (averaging about 48B).

This design makes LongCat-2.0 a "huge but sparse" model, offering the capacity of a massive system with the computational efficiency of a much smaller one.

Key Specifications:

Feature LongCat-2.0 Claim
Model Type Mixture-of-Experts (MoE) LLM
Total Parameters 1.6 trillion
Active Parameters ~33B–56B per token (~48B average)
Main Focus Agentic coding and long-horizon software tasks
Context Length Native 1M-token context
Training Data 35T+ tokens
Release Date June 30, 2026
Availability Open-source, online experience, API access, OpenRouter preview history

Unlike models trained primarily for benchmark-style code completion, LongCat-2.0 was pretrained from scratch to handle real-world, multi-step developer workflows.


Why is it Called a "Meme-Cat" Model?

The name LongCat directly references the classic internet meme "Longcat"—the famously elongated white cat from early web culture. While the model itself is a highly serious, trillion-parameter system, its playful branding creates an amusing contrast.

Essentially:

  • LongCat-2.0 is the serious underlying model.
  • Owl Alpha was its mysterious, stealthy mask.
  • The cat branding serves as a memorable, meme-friendly wrapper.

The Owl Alpha Connection

Before the official launch, developers using OpenRouter noticed a highly capable, fast, and anonymous model called Owl Alpha. It excelled at complex agent workflows, leading to rapid adoption.

Following the June 30 reveal, Meituan confirmed that Owl Alpha was indeed the preview version of LongCat-2.0. This stealth launch strategy provided three major advantages:

  1. Real-World Usage Data: Developers tested the model in practical, messy workflows rather than clean benchmark environments.
  2. Unbiased Evaluation: Users judged the model purely on its performance, free from brand bias or marketing hype.
  3. A Powerful Reveal: By the time Meituan claimed the model, it already possessed a proven track record and an active user base.

Why It Mattered on OpenRouter

OpenRouter is a popular API routing platform that allows developers to access various LLMs. Ranking highly there by call volume is a strong indicator of practical developer adoption.

During its stealth phase, Owl Alpha reportedly ranked first on Hermes Agent, second on Claude Code, and third on OpenClaw by call volume. This is particularly impressive because coding agents are highly demanding. To succeed, a model must successfully manage:

  • Massive context windows
  • Complex tool and API calls
  • Codebase navigation and multi-file editing
  • Multi-step planning and error recovery
  • Terminal outputs and dependency resolution

Architectural Highlights

LongCat-2.0’s architecture is optimized for agentic workflows through three core pillars:

1. Mixture-of-Experts (MoE) Routing

By activating only a fraction of its 1.6T parameters per token, the model routes specific tasks to specialized internal "experts." For example, different pathways can handle natural language explanations, code syntax, shell commands, or mathematical reasoning, optimizing both speed and accuracy.

2. Native 1M-Token Context

A native 1-million-token context window allows the model to hold entire repositories, extensive documentation, build logs, and long conversation histories in its active memory. To process this efficiently, Meituan utilizes LongCat Sparse Attention, which reduces the computational overhead typically associated with long-context processing.

3. Agentic Specialization

LongCat-2.0 is built for action. Instead of simply answering "Write me a Python function," it is optimized to execute complex instructions like: "Clone this repository, locate the bug, modify the necessary files, run the test suite, debug any failures, and commit the working fix."


The Domestic Compute Angle

A significant technical and geopolitical aspect of LongCat-2.0 is its training infrastructure. Meituan states that the model was trained and deployed on a 50,000-card domestic Chinese compute cluster.

As export restrictions limit access to standard hardware like Nvidia GPUs, this release serves as a major demonstration that frontier-scale, trillion-parameter models can be successfully trained and run on alternative, domestic AI ASIC architectures.


Pricing and Access

LongCat-2.0 is positioned as a highly cost-effective alternative to proprietary frontier models. Early pricing reports place its API costs at:

  • $0.75 per million input tokens
  • $2.95 per million output tokens

This aggressive pricing makes it highly attractive for developers running token-heavy agentic workflows.


Bottom Line

LongCat-2.0 is a powerful 1.6T-parameter open-source MoE model optimized for agentic coding, featuring a native 1M-token context window and highly efficient active parameter routing. By proving its capabilities anonymously as Owl Alpha before its official reveal, Meituan bypassed traditional marketing hype, letting the model's real-world utility speak for itself. It represents a major step forward for open-source coding agents and demonstrates the viability of training frontier-class models on domestic Chinese hardware.

Differences

The consensus answer is very credible.


  • No substantive contradictions between the responses.

Best answerOpenAI

Sources

  1. 1 LongCat-2.0: The Stealth AI Model That Was Quietly Topping OpenRouter All Along tech.yahoo.com
  2. 2 Meituan open sources LongCat-2.0, the 1.6T, near-frontier agentic coding model that's been leading OpenRouter — trained entirely on Chinese chips | VentureBeat venturebeat.com
  3. 3 LongCat-2.0: China's Most Unexpected AI Model geopolitechs.org
  4. 4 LongCat-2.0: China's 1.6T Open-Source Coding Model felloai.com
  5. 5 OpenRouter's Owl Alpha model hits 10.1T monthly tokens, ranks first globally cryptobriefing.com
  6. 6 Owl Alpha on OpenRouter Revealed as Meituan's LongCat-2.0-Preview with 11T Monthly Token Throughput | KuCoin kucoin.com
  7. 7 The True Identity of Owl Alpha on OpenRouter Revealed | Dayverse.id dayverse.id
  8. 8 Meituan LongCat-2.0 Powers OpenRouter Owl Alpha ... digg.com
  9. 9 Meituan releases LongCat-2.0 as open source, trained on 50,000 Chinese-made ASICs digitaltoday.co.kr
  10. 10 r/LocalLLaMA on Reddit: Introducing LongCat-2.0 - , a large-scale MoE language model with 1.6 trillion total parameters and ~48 billion activated per token. This was the stealth model that was on Openrouter under the name 'owl-alpha'. reddit.com
  11. 11 youtube.com vertexaisearch.cloud.google.com
  12. 12 binance.com vertexaisearch.cloud.google.com
  13. 13 reddit.com vertexaisearch.cloud.google.com
  14. 14 opensourceforu.com vertexaisearch.cloud.google.com
  15. 15 venturebeat.com vertexaisearch.cloud.google.com
  16. 16 geopolitechs.org vertexaisearch.cloud.google.com
  17. 17 scmp.com vertexaisearch.cloud.google.com
  18. 18 reddit.com vertexaisearch.cloud.google.com
  19. 19 longcatai.org vertexaisearch.cloud.google.com
  20. 20 zenmux.ai vertexaisearch.cloud.google.com
  21. 21 reddit.com vertexaisearch.cloud.google.com
  22. 22 longcatai.org vertexaisearch.cloud.google.com
  23. 23 longcatai.org vertexaisearch.cloud.google.com
  24. 24 github.com vertexaisearch.cloud.google.com
  25. 25 emergentmind.com vertexaisearch.cloud.google.com
  26. 26 longcatai.org vertexaisearch.cloud.google.com
  27. 27 remio.ai vertexaisearch.cloud.google.com
  28. 28 lmsys.org vertexaisearch.cloud.google.com
  29. 29 longcatai.org vertexaisearch.cloud.google.com
  30. 30 youtube.com vertexaisearch.cloud.google.com
  31. 31 venturebeat.com vertexaisearch.cloud.google.com
  32. 32 explainx.ai vertexaisearch.cloud.google.com
  33. 33 llmreference.com vertexaisearch.cloud.google.com
  34. 34 longcatai.org vertexaisearch.cloud.google.com
  35. 35 reddit.com vertexaisearch.cloud.google.com
  36. 36 huggingface.co vertexaisearch.cloud.google.com
  37. 37 longcat.chat
  38. 38 LongCat-2.0 Released: Trillion-Parameter Agentic Coding Model on Domestic Compute | LongCat AI longcatai.org
  39. 39 LongCat-2.0 - 1.6T Agentic Coding LLM | 1M Context, Open Source | Meituan AI longcatai.org
  40. 40 Introducing LongCat-2.0 longcat.chat
  41. 41 LongCat-2.0: The Stealth AI Model That Was Quietly Topping OpenRouter All Along - Decrypt decrypt.co
  42. 42 LongCat-2.0 - 1.6T Agentic Coding LLM | 1M Context, Open Source | Meituan AI longcatai.org
  43. 43 Meituan Opens LongCat-2.0 Coding Model With 1M Context winbuzzer.com
  44. 44 Meituan open-sources 1.6-trillion-parameter LongCat-2.0 AI model trained on Chinese chips - Cryptopolitan cryptopolitan.com
  45. 45 Meituan Trains 1.6T LongCat-2.0 End-to-End on Chinese Chips | AI Weekly aiweekly.co
  46. 46 Comfyui-wiki comfyui-wiki.com
  47. 47 LongCat AI - LongCat-2.0 Trillion-Parameter Agentic Coding Model | Meituan longcatai.org

Cite this answer

consens.io. (2026-07-03). Consensus answer to "LongCat-2.0 Explained: The Meme-Cat Model That Secretly Topped OpenRouter as Owl Alpha". Models consulted: OpenAI: GPT-5.5, Mistral: Mistral Medium 3.5, Anthropic Claude: Claude Opus 4.8, Google Gemini: Gemini 3.5 Flash, DeepSeek: DeepSeek V4 Pro, Grok: Grok 4.20. Consensus model: gemini-3.5-flash. Sources: https://tech.yahoo.com/ai/gemini/articles/longcat-2-0-stealth-ai-201855556.html, https://venturebeat.com/technology/meituan-open-sources-longcat-2-0-the-1-6t-near-frontier-agentic-coding-model-thats-been-leading-openrouter-trained-entirely-on-chinese-chips, https://www.geopolitechs.org/p/longcat-20-chinas-most-unexpected, https://felloai.com/longcat-2-0/, https://cryptobriefing.com/openrouter-owl-alpha-model-global-ranking/, https://www.kucoin.com/news/flash/owl-alpha-on-openrouter-revealed-as-meituan-s-longcat-2-0-preview-with-11t-monthly-token-throughput, https://dayverse.id/en/articles/true-identity-of-owl-alpha-on-openrouter-revealed/, https://digg.com/tech/xykvwcr3, https://www.digitaltoday.co.kr/en/view/76555/meituan-releases-longcat-2-0-open-source-trained-on-50-000-chinese-asics, https://www.reddit.com/r/LocalLLaMA/comments/1uj7egu/introducing_longcat20_a_largescale_moe_language/, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFyrIvmsQ2b4byISFLnb08vvFwuwA2CgIKzohsvzAdiSMhphver4xrx9XQX5s55V3SwJ6VBnCoSmsqlGMO84Z0Yr2XSGBGz3o8Tz62MVvy-ru-lcZMGR8N3OsuI6OUs4Lr4, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEg6SXDYxpz0DrdYmdF45VQx4YvvTNh0dAu-K7MiRcJXkAkAOnH2g_fZyTNY1-UB0EiCwcvEhdObmjFBJZrEzNCxHhbBj0MOoFjcBfP5U_0TqrImYhvSMyCsLb7eK8j-4cTa02157inkqd_-A==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHXzJA_Kj_TYsjBrK7MXkKfRQA8kaXwn9jFOBOZDVq-J38NoHmk9KOgqkncJ2Rqgl6OYLza67AwNscAfLm4aKuhNe3LDXZRTFiNF8pjL5J7P8twgP_xN-1D03EBbZgGbFjn8uKAOURTt095f6UX9OBXgO2laNxUOfVJ7o-ZNy9c2BhU4ykrbhLhUbuNXokYb7QAaA==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHEDdQ68Iwn_CMgpN3uZIzEsllqJ7P8eqJ7moDiisSVI9YVvnvCywOaskZrlgErbAEblfaxPmo744isMV-ZRHYmHnmrufGK0hEVymZocLGOd3BmN-CgriimP6i6CE9Fp2V1aAZMxa9eg1_SlTVkqXnjrxjI1tt6W9b9vdJ-tAaYp-VmbEFaBrmvVGvLYv_Bh1U=, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFhfsWaFjz7ip_IFFJv53BB6_tdsAxhznzTZWLyAMUTIYxt6JLt_phpVZATCdpbBHTE6TTz2NSoHP2yx8rZyPgKFumcCt-vPfcwBzmzv1vcF2aGHlhJFFC_5EL8VpQgOc23uxUuERr5VEOAtAnatQS8LEn8N5KqFAlZWUUUAjjq3Lw1XCXiqDxZ4jT8SYX44Y12QPVSMi_DfA_ZGVFatnAauTLsLfE29mVzcV4TIOppv2Y9Ntvx0hMfsz9niYqobF9qE7TAQKXavBGJwu8g5Gb1L4v1cFuVK9SKwJFIiGNCPJbmhAhm2Q==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEZROqqS6TQSe6VUhoA4-TNDyj22TXRgaYYaFuK3v2xrXyY05CWQ_hfwQjIiMlZ6QkASF0mVHlNgOAVxmP81Cozj02Qh6EQ_6RZGkZUjiP8tqiOXK4U_302E1bfX7HAaip7hjiacZ9OoJjUGHgSpmBsUIrGM54v, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQESO3pjgjX0TlPNPTPk8Lbnb8aofObMzDgIe_AsarEjbBhWpIyJXSubSqIXh94rSAtMYbKyENUZSL3XHtzxvyz0-7Xp5DIDw1jS1XizhGbR__OVeo4a8WHSiIjcLIKzmcRgkBMB2ZSMkoymdz24kVMAjFJn80pm55zGBdPpVCKW_O0st5TVgjy1MMwjoXXuRYRNgYkzmsmdxYx3AiXTvXVrfApR9nhIY7THCp_B41eNBTmq8Zlwk8MmgpA=, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE_3u4sD0Vn_mHKptDUkeeeTEpw3Jt3lBBl_ElPMFFwL_h0m3EralalTIp7oQHRbP7BNpS_-s7l8f7xyXcdWKK2gXvWoLsZOfSyRcabxvJClQD3ENOIMeVgidjdiYKZsy2dOGOT_YOhzcvisqeHGtX5V_lgqygHm6VjvQ9DFeDhxOorPL1PdjeTGpzTG2cYE51Ku2qiVsEkJNf-kg==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFzLOdfiqNkdXBLiaQCCRb3vDR3nz3m1deIxYCFd76WQT11BkF1p5svMPusso-i9awFceSHW-yWr38iYuimXMZWYdkU2f1jjNXjf3i2PrPbrUXszMfeCsqH4F9Hv5mK, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEkweO5GpOCfuw1U6b8e0fZF0w5u57JlF0hBznAYjQvgafH9i3oztDXeayB6FrRL9rrpv4nRrPELumHj6vJLhnlwRT-77WJ82syJ8bDY0nB83ABlyuOboPMfLIf, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGTjLYZVZPYqyHdT0vwibOoEjbtBFZYsXDTbAucovwM4UOikz4CPDZKPPwkFoHwgdOe9jvN4-uFa4rILNaMOXTDhYfsyZ7Y0aBIOzM8KNp00R4zj4VdAmQ-JDsLMXsMLuguyskyUOFWvnuVOrJ69yeWn8NVJp4ZGAE3JsIg5RAAsd-lZlcsUSB7K0BHAGnvCw1HHacnCJsxolbusg==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF4KUU2KAfQFXeef3G-hNK95HvP-vhNJ3WqOKyWPF-z1EPAIkd7m6Q01rLIa48JygcihDI0nL5aI-iFKYiahN1mZzCqmDLzXVxQpNwoK6xr7aMFrrkBLJufHujJPp1cgE0=, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEABrbE_ICMWLitTXbFdjhwtO9fwi98meu7FUfCMIC8Z2M5cwbQlLnDHKn5MW0ok7aKdDH_aHiL3w49EvTHeSu7JqJ6aSerXi4HIt32--pqPhb2t5qQCNdhAFM5satDTYE=, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGOqnDvTY-8gaewVXYcmS_GThW4HZA4zPfhIe2wpbUYqtJjLWu6dj4xqFy4aLEtrhb8X-paLxoSHnBJeWopjLwKponO3wt5MQXM754qOUI6QFGsx77QlsNiKAQU28GqykMS1tpRxkwEg-e1, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF1zkJQiUHZJGXrpM6BYwnMo0xMN26Dllx3srz6va4ttNkodCxA4m0qVsPZzcluxeqxuOtGZlpBvPqV5BhdQ15tsLmIOiBwi33zgGIUZUywxZEjPJ0T0p1BxOOmhybF-oEuSnLw7CKzGc1HNeuVUQp2WUM2hA==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHx9L2Aqu1omWk7aTUfApV5YzV0dmRCZy5uhlNT8jK8Q2xrxoc0otaDs-vY4Upwm3pXxhHR8LQEvMOhMjxHZmlG4n3bS5DuXI0LxlE4MT2Fncd1DWyht74JFzHLOPw=, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFmL319UL2fuCiLESGNGCTltmFy_oSaHCm-xmCQI5i9S06B_6ZGkQxCQqShKIJpo0GLYlHz5N4MPTY0yDjCJneDZ17Ju1L-moTOCBl6as_iK83R_rzKvo_1msyY-vy9bufRtQWzir6cg-7G6FW5hRvZ8zpLmeI8n3CH5h9Yp-CF7dwL, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFufIldB8hIiLPg4RuAFfrwXf7z_nJWbR4L79Q_vfB9yM6TYoEoJVVtTidQgJrX_almXL9NIgLxLPBIQz2DCa6Ns3t220StlUUp_7503HhMQF_utJwmtC5J3nuwIR2urpmFt15CnqfpLW9LPPSyzyas, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEayUVx7Knvaa2WlfS4g4Rraya5AwXdlbhM63fjjUBAByvJcEt67EzisC0Eij0n9LTGAbuHC1yq3TbDBQI2v-44DH32VC_F-kvrqSOUCjcphSb4m0HKwoYkLzSn2WTG, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGUXQhWCpG-0sIJ2FSUwCWWaKF9Q_OtuJd9OxkAwfgNApgi9TDM59heTdtjUXv1AjDSZIykMedPL89p-485oyfRf-ZK7spAgsK4-OHFFlFZ8AaaCcOwah0GvAKSvsJEnnGw, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGzZhe9DUHcpuXFQy9vnSKeAyph684VHZ1fuxsGZ-vvnbUiUNrCPL_nHt0U0Ko1UZp4FK9vsg52ITZ_T_0HK0jQOJWD3MB9GdUR169NXmzFxfnHUDGLW2LGdUf5I3LtT8xIRDUsJMcoC4a1_yJfV_sDqSpp7Kx0oeE_1vVNtnCF7fdhBLRWYTShCWyQQ3I9rMlYpEIoLe81GalSuMwFKhDe-Gz9x45VhHlXgRSMJH_hyrmM5Ub4lYc8tE8UpT0p2ij6cxMS23fEbHMwkwx2qyhpBvUkqmehYwmUqqH_UMrbMhTuhMZP9g==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE4cGUvjbOhDoGffLZJvr2GEqoIIRDLYgekVp12Y9YsToIGGPy3NwBPDtxP-VX0E-68N55yIUsA6xUH2Q1PNSyr65JY3a9n_RTVn0cdv3UwzgoXgzwxjTdhKBT4BcMXQGCx5OHbDIzBzAysv3qv6N68Xt8m7M2suE_pJ8w=, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH_Qb9jtMBv9Q0XYHXAyYUOFLjfWxqHxOod-2CZipWIfVr9sgbJmndqR35FIGo9qU8HzuPjlzqXHcL5WGbb4teIrlMHSeINotzK4-VpEKZ4YqnztQrdd_c5T5AQalS0CA_2RK8=, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF418m3HPlCvoE_C9rbzD-BZavXwhp9lpdEz6tUhrdC0lFapbRvyGolZobW9bcctkisOh4CeRYPIAHHw6qrpuOmfQ2EEIkoiXYcmwhPKaPJ, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEEjaA4BqHPTSblJXWv6ksohgIV5e4RwpPQKSGum3xrDD0xZgusTCVv8wUYvWGULevcmOEkTAjLfi6HnK-2MQ5VgrXJ3CniNLZgeoAdK_qxumJxiH5DsVTNXCgHay-3_Ddun6MpsBavfon8jXVzjcvDD6EsqmxAH_uKaLsAnPrti7xpoL3S3ROVReMzSpTpJuNvMZBIOOjISaJS, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGfE0Q1wCIGY0-pYR96go225-Rq4z_XWcwK7DrwvY-MkbeMomYTquTecgqo4KAkdKmNuy8sR1GhbCLKyazSzAsSJAleNp8QXEP35Lo1e1o2IFpsDaToFh5wJh0KGqO0lJcUeWt5VQGX, https://longcat.chat/blog/longcat-2.0/, https://www.longcatai.org/news/longcat-2?utm_source=openai, https://www.longcatai.org/models/longcat-2?utm_source=openai, https://longcat.chat/blog/longcat-2.0/?utm_source=openai, https://decrypt.co/372579/longcat-2-0-meituan-ai-stealth-model-openrouter?utm_source=openai, https://www.longcatai.org/models/longcat-2, https://winbuzzer.com/2026/06/30/meituan-opens-longcat-20-coding-model-with-1m-context-xcxwbn/, https://www.cryptopolitan.com/meituan-longcat-2-0-ai-model-chinese-chips/, https://aiweekly.co/alerts/meituan-trains-16t-longcat-20-end-to-end-on-chinese-chips, https://comfyui-wiki.com/en/news/2026-06-30-longcat-2-moe-meituan, https://www.longcatai.org/ Retrieved from https://www.consens.io/s/longcat-2-0-explained-the-meme-cat-model-that-secretly-5v67BrOHEnyVPoSw

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