Moonshot releases Kimi K3 open weights amid license debate

Moonshot AI has published Kimi K3’s open weights and technical report on Hugging Face. Kimi K3 is a 2.8T-parameter MoE model with 104B active parameters, native vision support, and a 1M-token context window. It stands out as one of the largest open-weight releases to date, but the model’s deployment cost and its commercial licensing terms quickly became as notable as the model itself.

Confirmed

• Moonshot describes Kimi K3 as a 2.8T MoE model with 896 experts, activating 16 experts per token for 104B active parameters.
• The technical materials highlighted in posts say K3 introduces Kimi Delta Attention, Attention Residual, and a three-axis scaling design across sequence length, network depth, and model width. A lower-bounded decay floor of -5 was also added to chunkwise KDA to reduce finite-precision overflow issues.
• Posts relaying the technical report say K3 scored 91.2 on BrowseComp. The same report was also described as finding 16 previously unknown vulnerabilities across six projects, including two Linux kernel vulnerabilities.
• Community deployment estimates put the weights at about 1.4TB. One widely shared calculation said fully fitting the model would require at least 18 GPUs, or 8 B300 cards; Reddit users argued that even multi-node local workstations built around 2–4 RTX 6000 Blackwell systems would still struggle to run it natively.
• The model uses a Modified MIT license. Posts summarizing the terms say local self-hosting is allowed, but if Kimi K3 is resold as a cloud or Model-as-a-Service offering by a company or affiliate with more than $20M in revenue over any rolling 12-month period, a separate agreement with Moonshot is required.

Unconfirmed

• Beyond the reported benchmark and security results, Kimi K3’s real-world general-purpose performance still needs broader independent testing.

Why it matters

• Kimi K3 pushes the scale of open-weight releases into the 3T class while combining long context, multimodality, and agent-oriented positioning, making it a notable signal in the frontier model race.
• At the same time, the release exposes a familiar tension in open-weight AI: the model is publicly downloadable, but the hardware needed to run it is out of reach for most users, and the commercial terms sparked pushback. In particular, @Eyelbee argued that the licensing and pricing implications make third-party inference economics look too close to a closed API, weakening the practical openness of the release.

2026-07-26 ~ 2026-07-28 · 155 related posts

Full story(5 episodes)→

• Episode 1: Moonshot's Kimi K3 Set for Release with Multi-Platform Support(2026-07-24, 4 posts)
• Episode 2: Moonshot AI Unveils Trillion-Parameter Kimi K3(2026-07-24, 4 posts)
• Episode 3: Kimi K3 Open Weights Launch Draws Instant Ecosystem Support(2026-07-26, 24 posts)
• Episode 4: Moonshot releases Kimi K3 open weights amid license debate(2026-07-26, 155 posts)
• Episode 5: Moonshot's Kimi K3 Tops Hugging Face Trending(2026-07-27, 5 posts)

• Moonshot AI Launches Open-Weight Kimi K3 to Rival Top US Models — emmanuelvivier · 2026-07-26
• Moonshot AI launches open-weight Kimi K3 and claims strong results against top US models — emmanuelvivier · 2026-07-26
• Moonshot’s Kimi K3 ships open weights, but self-hosting needs 1.4TB and 18+ GPUs — Common_Dream9420 · 2026-07-27
• [source] Kimi K3’s 1.4 TB weights fit only on 8×B300, not A100 or H200 — qubridInc · 2026-07-27
• Moonshot AI publishes Kimi-K3 on Hugging Face — mervenoyann · 2026-07-27
• Kimi-K3 is now live on Hugging Face — himanshustwts · 2026-07-27
• Kimi K3 weights are now available — SavunOski · 2026-07-27
• Moonshot makes Kimi K3 officially open weights with a 1M-token context window — scaling01 · 2026-07-27
• Moonshot releases Kimi K3, a 2.8T multimodal MoE with 1M-token context — 月之暗面 Kimi · 2026-07-27
• Moonshot's Kimi K3 repository goes live with a 2.8T-parameter model card — tokenbender · 2026-07-27
• Kimi K3 adds native MXFP4 quantization and shows heavy VRAM demands — teortaxesTex · 2026-07-27
• [source] Moonshot's Kimi K3 license allows broad use, but adds commercial thresholds above $20M — natolambert · 2026-07-27
• Kimi K3 License Breakdown: Non-Commercial Limits for Firms Over $20M Revenue — natolambert · 2026-07-27
• Kimi K3 hardware estimates point to 480 GB VRAM and 8× H100 setups — cedric_chee · 2026-07-27
• Moonshot publishes Kimi-K3 on Hugging Face with 2.8T parameters and 1M context — BankApprehensive7612 · 2026-07-27
• Hugging Face model card details Kimi K3’s 2.8T-parameter multimodal setup — op7418 · 2026-07-27
• Moonshot opens Kimi K3 weights and report, citing a 2.8T MoE model — eliebakouch · 2026-07-27
• Moonshot launches Kimi K3 with 2.8T parameters, 1M context, and native multimodality — mervenoyann · 2026-07-27
• Kimi K3 license sets $20M/year inference terms and a separate $20M/month product deal — natolambert · 2026-07-27
• Kimi K3 weights are now available on Hugging Face — inductionheads · 2026-07-27
• Kimi K3 is now available on Hugging Face — Kyrannio · 2026-07-27
• Moonshot says Kimi K3 is now out — _akhaliq · 2026-07-27
• Moonshot’s Kimi K3 report says its largest model has 2.78T parameters and 2.5× better scaling — teortaxesTex · 2026-07-27
• Kimi K3 License Analysis: Large Enterprises Require Specific Commercial Deals — himanshustwts · 2026-07-27
• Moonshot’s Kimi-K3 model page is now live on Hugging Face — iamfakhrealam · 2026-07-27
• Moonshot updates Kimi K3 license but withholds day-one support for workers.ai — michellechen · 2026-07-27
• Cloudflare adds Moonshot’s Kimi K3 to AI Gateway, but Workers AI lacks day-one support — michellechen · 2026-07-27
• Kimi K3 triples parameters and doubles active experts in a new MoE design — teortaxesTex · 2026-07-27
• Kimi K3’s 2.5x scaling-law gain draws praise for training efficiency — andrew_n_carr · 2026-07-27
• Moonshot releases Kimi K3 report, claiming 2.5× scaling-efficiency gain over K2 — cedric_chee · 2026-07-27
• Kimi K3 reportedly improves training efficiency by 2.5× — zephyr_z9 · 2026-07-27
• Kimi K3 moves from MIT to a new license tied to MaaS revenue thresholds — AdinaYakup · 2026-07-28
• Kimi-K3’s license is free for self-hosting, but clouds must share profits — scaling01 · 2026-07-28
• Kimi K3 report says numerical stability remains a hard problem at scale — teortaxesTex · 2026-07-28
• Attention Residuals may expose cross-layer information flow directly for interpretability — tokenbender · 2026-07-28
• Kimi K3 claims 2.5× better scaling efficiency with a three-axis architecture — suchenzang · 2026-07-28
• K3 Architecture Enables Direct Observation of Cross-Block Routing for Model Interpretability — tokenbender · 2026-07-28
• Moonshot’s Kimi K3 lands on Hugging Face as a 2.8T MoE open model — gaganghotra_ · 2026-07-28
• Kimi K3 arrives as a 2.8T MoE with 104B active params and a 1M-token context — stochasticchasm · 2026-07-28
• Kimi K3 report omits hardware details, leaving its 2.5× efficiency claim hard to verify — cedric_chee · 2026-07-28
• Moonshot Releases Kimi K3 Tech Report, Cites 2.5x Scaling Efficiency Gain — cedric_chee · 2026-07-28

9 near-duplicate retellings: teortaxesTex · HarveenChadha · _akhaliq · iamfakhrealam · ricklamers · cyb3rops · ns123abc · FlorianGallwitz · andrew_n_carr