Moonshot Releases Full Weights of Kimi K3: The First 3T-level Open Source Model
On July 27, 2026, Moonshot AI released the full weights of Kimi K3 on Hugging Face and GitHub: it has a total of 2.8T parameters, 104B activations, and a 1M context window, adopting MoE + KDA attention and MXFP4 native quantization. This article sorts out the architecture specifications, coding evaluation performance and vLLM self-hosting key points, and discusses the gap between open-source weights and closed-source cutting-edge models as well as the deployment threshold.
Read MoreAlibaba Releases Qwen 3.8-Max: 2.4T-Parameter Max-Level Model Open-Sourced for the First Time
On August 3, 2026, Alibaba Cloud officially launched Qwen 3.8-Max: a sparse MoE model with 2.4 trillion total parameters and 95 billion activated parameters, featuring a 1-million-token context window and multimodal input support. This marks the first time a Qwen-Max series model has promised open-source weights, and it is expected to be available on Hugging Face and ModelScope next week. The API has already gone live on QwenCloud, Model Studio, and Vercel AI Gateway (alibaba/qwen3.8-max), and supports Agent tools such as Claude Code and Codex. This article sorts out the verified specifications, key long-range Agent capabilities and access methods for developers to evaluate and call, or wait for self-hosting.
Read MoreMoonshot Open-Sources 2.8T-Parameter Kimi K3: The Largest Open-Weight State-of-the-Art Model to Date
On July 27, 2026, Moonshot AI released the full weights of Kimi K3 on Hugging Face: with a total parameter size of 2.8T and 104B activation per token, the MXFP4 format weighs approximately 1.56 TB (split into 96 safetensors shards). The official claims it is the world's first open 3T-level model. This article sorts out its Stable LatentMoE architecture (896 choose 16 experts), KDA attention mechanism, 1-million-token context window, MoonViT-V2 multimodal capabilities, as well as self-hosting thresholds and API access methods, for developers to evaluate deployment and integration solutions.
Read MoreMoonshot Open-Source Kimi K3: An Open-Source Cutting-Edge Model with 2.8T Parameter MoE, 104B Activations and 1M Context Window
On July 27, 2026, Moonshot AI released the full weights of Kimi K3 on Hugging Face and GitHub: a 2.8T total parameter MoE model with 16 activated experts out of 896, 104B activated parameters, 1 million token context window, and native multimodal capabilities. Based on the official README and arXiv technical report, this paper sorts out the key points of the KDA and Stable LatentMoE architectures, interprets the differences between Agent evaluations such as Terminal-Bench and model harness tests, and introduces the API, deployment paths via vLLM/SGLang, and the usage boundaries of the Kimi K3 License.
Read MoreAlibaba's Qwen 3.8 2.4T parameter preview goes live, "open-sourced weights coming soon" becomes a suspense
On July 19, 2026 during the WAIC conference, Alibaba's Qwen team released the 2.4-trillion-parameter multimodal preview version Qwen3.8-Max-Preview, claiming that its capabilities are second only to Claude Fable 5, and promising that the open-weight release will arrive "soon". Unlike Kimi K3, which came with benchmark results and a clear open-source timeline, this announcement lacked evaluation tables, model cards, and a weight open-source schedule. This article cross-verifies official and media reports, sorts out the MoE architecture, Token Plan/Qoder access methods, the changes in Qwen's flagship open strategy, and guides developers on how to distinguish between "verifiable facts" and "manufacturer positioning" to rationally试用 this still-iterating preview endpoint.
Read MoreKimi K3 Open-Sourced Weights Deployed, Competition Among Chinese Open-Source Large Models Heats Up Again
On July 27, 2026, Mooncake AI officially released the full model weights of Kimi K3. As the world's first 2.8T-parameter open-source MoE model, it supports 1 million-token context window and native multimodality. The single post on Hacker News gained over 600 upvotes, sparking heated discussions in the community regarding its performance comparison with Claude Fable 5 and the distillation controversy. This article sorts out the architecture specifications, benchmark positioning, the background of Alibaba's 36% shareholding, as well as developer guides for API and local deployment of Kimi K3.
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