Releases from frontier labs, major companies and research institutes — grouped by model, deduplicated across HuggingFace, OpenRouter and official blogs.
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Moonshot AI🇨🇳Frontier
Open-weight, natively multimodal MoE model with 2.8T total and 104B active parameters, aimed at agentic tasks such as coding, 3D creation and financial research. Artificial Analysis scores it 55 against 58 for Claude Opus 5.5.
Moonshot AI🇨🇳Frontier
Kimi K3 is an open-weight multimodal model with 2.8T total parameters (104B active) and a 1M token context window, built for long-horizon coding and agentic knowledge work. Moonshot claims about 2.5x better scaling efficiency than Kimi K2.
Moonshot AI🇨🇳Frontier
Kimi K2.7 Code is Moonshot AI's coding-specialised agentic model. It accepts image input and tool calls and can handle complex software-engineering workflows end to end. It scores 62.0 on Kimi Code Bench v2 and uses about 30% fewer thinking tokens than its predecessor K2.6. It trails GPT-5.5 slightly on coding benchmarks but beats Claude Opus 4.8 on MCP Mark Verified with 81.1.
Moonshot AI🇨🇳Frontier
Multimodal predecessor of K2.7-Code — Visual Agentic Intelligence with 1.1T parameters. 2.66M HF downloads. Still relevant for multimodal tasks (images, video) since K2.7 is code-only.
Moonshot AI🇨🇳Frontier
Moonshot's 'Visual Agentic Intelligence' — 1.81M HF downloads. Basis for K2.6 and K2.7. One of the first large models with real multimodal agentics at 1T parameters.