Alpha
Ctrl K
Contact
Support · Kimi K3

Will it last?

Ownership levelPartialnone·limited·partial·substantial·fullAnalytical input D ยท 53.2/100

This page is a projection of the one entry record, the Transparency factor that Support covers. The full verdict is set by all four factors together, floor-weighted so the weakest caps the whole.

Which domain expands which factor
  • AssessUse & modify + Transparency
  • ImplementData control + Reliability
  • UseReliability
  • SupportTransparency

Common problems & fixes

Aggregated pitfalls for a 2.8T-parameter MoE: multi-node out-of-memory and sharding mis-configuration, MXFP4/MXFP8 kernel-to-engine version mismatches, and checksum or revision drift on download. Pin the revision, verify checksums, and match engine and kernel versions to the card's documented stack. This is not an exhaustive catalogue.

Versions, changelog & cadence

Kimi K3 ships as a single checkpoint on the verified moonshotai org (announced around 2026-07-17, open weights around 2026-07-27). There is no Base/Instruct/Thinking split. The Hugging Face revision hash is the changelog anchor; pin it.

Community & support channels

Support is the general Moonshot presence: the moonshotai Hugging Face org (model discussions) and the MoonshotAI/Kimi-K3 GitHub repository (issues and the technical report). There is no dedicated support SLA.

Tracked known issues

From the model card and technical report: no built-in safety with documented offensive-cyber willingness, undisclosed training data, code and compute, and the operational burden of a 2.8T-parameter model with no small variant. Track these against your own control stack rather than a published issue tracker.

How this scores

The ownership factor this domain covers, drawn from the one entry record.

2

TransparencyDo you know what it is: weights, training, behaviour, and legible terms?

Moderate

You can inspect the weights and read a detailed technical report, but the training corpus, the training code and even the training-token and FLOP figures are closed, so you cannot see how it was made or reproduce it.

How this scores (AOI sub-dimensions)
Provenance3/5how well we can trace and verify what went into the modelDistributed from the verified moonshotai org on Hugging Face as native MXFP4/MXFP8 weights (not pickle) with the canonical source clear and no malicious-mirror incident on record (checklist ~4/8).
Governance3/5how accountable and well-documented the publisher isActive, accountable publisher (Moonshot AI) with a detailed technical report and a verified hub presence, but the report is a GitHub PDF rather than an archival venue, there is no documented vulnerability-disclosure or deprecation policy, and there is no EU Code of Practice signature.
What this means for adoptionYou substantially use, modify and commercialise the self-hosted Kimi K3 weights and run them entirely on your own infrastructure, so your data stays yours - but ownership is only partial. The custom, non-OSI licence adds a $20M Model-as-a-Service separate-agreement gate on top of the branding threshold, the training corpus/code/compute are closed, and, most consequentially, the model ships with no safety tuning or guard while its own report shows it performing offensive-cyber tasks that frontier labs refuse. Self-host behind a full external control stack, keep off the train-by-default hosted API if data control matters, and confirm the LICENSE and the Model-as-a-Service threshold before commercial deployment.

Sources

The same evidence records as the entry sheet. Read means the text was verified; unverified means it is known to exist but not yet read.

Model cardread2026-07-28
Kimi K3 model card on the verified moonshotai Hugging Face org: 2.8T total / 104B active MoE (16 of 896 experts), 1M context, MXFP4 weights / MXFP8 activations, native text+image+video, serving on vLLM/SGLang/TokenSpeed; no training data/code/tokens or safety tuning disclosed.
Licenceread2026-07-28
Kimi K3 License, read verbatim via the raw mirror: grant to use/copy/modify/merge/ publish/distribute/sublicense/sell, plus a Model-as-a-Service separate-agreement requirement over $20M aggregate revenue in any consecutive 12 months, plus a 100M-MAU or $20M-monthly- revenue "display Kimi K3" branding clause; internal-use and official/certified-partner exemptions; not OSI-certified.
Technical_reportread2026-07-28
Moonshot's technical report "Kimi K3: Open Frontier Intelligence" (GitHub PDF), read: 2.8T/104B MoE with Kimi Delta Attention and Per-Head Muon; context curriculum 8K to 64K (pretrain) and 256K to 1M (cooldown); no total training-token count and no absolute pretraining-FLOP figure stated; section 6.2.2 documents offensive-cyber capability (Tier-1 vulnerability discovery, Tier-2 exploit development) and notes Anthropic/OpenAI models refuse such tasks while K3 does not.
Terms of serviceread2026-07-28
platform.kimi.ai model-use agreement, read: user Content may be used to develop and improve the Services, with opt-out only via an enterprise arrangement on request; governed by the laws of Singapore with SIAC arbitration.
Privacy Policyread2026-07-28
platform.kimi.ai privacy policy, read: the hosted service trains on user prompts, audio, images, videos and files by default ("helps us optimize our models"); controller MOONSHOT AI PTE.
Third-party analysisread2026-07-28
Reputable coverage (Tom's Hardware) of the 2.8T Kimi K3 release: architecture (16/896 experts), MXFP4/MXFP8 QAT, K2 comparison, 1st place on the Frontend Code Arena, and positioning behind only Claude Fable 5 and GPT-5.6 Sol overall while ahead of other open models on coding and agentic benchmarks.
Third-party analysisunverified2026-07-28
No public EU AI Act training-content summary, copyright policy, or provider documentation package is published for Kimi K3, and the training corpus, training code and training-compute figures are not released.