Five days to weight drop · Modified MIT · 2.8T MoE · 1M context · 1.4TB @ 4-bit · API $3/$15
Direct answer: Moonshot AI will release the full weights of Kimi K3—a 2.8-trillion-parameter MoE model with a 1,048,576-token context window—on July 27, 2026, under a Modified MIT license on Hugging Face, alongside a technical report. The API and Kimi product stack went live July 16. This guide covers timeline confusion, specs, benchmarks vs Claude Fable 5 and GPT-5.6 Sol, real API cost with caching, self-hosting hardware reality, industry impact, and a release-day checklist—without pretending you can run it on a laptop.
Bottom line: K3 is not a “Fable 5 killer.” It ranks third on the AA Intelligence Index (57.1 vs 59.9 / 58.9), but delivers frontier-adjacent capability at roughly one-third the cost, plus two things closed models cannot offer: downloadable weights and a 1M-token context window.
Two launch dates: API live ≠ weights downloadable yet.
“Run locally” clickbait: ~1.4 TB at 4-bit, 64+ accelerators—not Ollama-on-a-laptop territory.
Closed-model premium: Fable 5 per-task cost is ~65.8% higher (AA measured K3 at $0.94).
Long-context KV cost: Many models advertise long windows but cannot afford them in production.
Regulatory off-switch: Closed weights can be pulled; published open weights cannot be “un-released.”
| Date | Event |
|---|---|
| 2026-07-16 | API + Kimi stack live; Artificial Analysis benchmark |
| 2026-07-17 | WAIC; national-milestone framing |
| 2026-07-27 | Hugging Face weight download + technical report |
Search intent peaks on kimi k3 release date, kimi k3 download, and kimi k3 hugging face around July 27. Update dateModified and swap “scheduled” copy to “now available” within hours of the drop.
| Spec | Value |
|---|---|
| Parameters | 2.8 trillion (largest open-weight release to date) |
| Architecture | Sparse MoE: Stable LatentMoE, 16 of 896 experts active per token |
| Attention | Kimi Delta Attention (KDA) + AttnRes + Gated MLA |
| Context | 1,048,576 tokens |
| Modalities | Native vision (text + image; video in product); text out |
| Weight format | MXFP4 weights + MXFP8 activations (native low-precision training) |
| Scaling vs K2 | ~2.5× efficiency at equal compute |
| Long-context decode | Up to 6.3× faster at 1M tokens (KDA) |
| Model | AA Intelligence Index |
|---|---|
| Claude Fable 5 | 59.9 |
| GPT-5.6 Sol | 58.9 |
| Kimi K3 | 57.1 (#3 of 189) |
Moonshot unusually admitted trailing Fable 5 and Sol overall, citing harness sensitivity and over-eager behavior on ambiguous intent. Benchmarks ran through different harnesses (eval date: July 16, 2026)—treat as directional until independent reruns land.
| Item | Price per 1M tokens |
|---|---|
| Input (cache miss) | $3.00 |
| Input (cache hit, automatic) | $0.30 |
| Output | $15.00 |
Use open weights in titles and snippets—not “open source” alone. K3 releases weights + a technical report under Modified MIT; training code and data are not fully open. That distinction matters on r/LocalLLaMA and HN, and it is itself high-intent FAQ content for is kimi k3 open source.
On July 27 expect: Moonshot Hugging Face org upload, LICENSE text, vLLM KDA/prefix-cache support aligned with partners, and later Ollama/GGUF builds following the K2 pattern.
Honest answer: not on consumer hardware.
HF repo completeness (shards, index, config)
LICENSE verbatim (Modified MIT terms)
Quantized artifacts (MXFP4 / GGUF)
vLLM / SGLang launch commands and minimum hardware notes
Independent long-context and BrowseComp reruns
Frontier gap nearly closed: AA spread shrunk to a few points—harder to justify closed-only premium on raw capability.
Geopolitics: WAIC timing; US briefly delisted Anthropic Fable/Mythos (restored July 1)—regulators can block closed API access, not already-published weights.
Chinese wave: GLM-5.2, DeepSeek V4 Pro (1.6T), MiniMax—K3 is the peak of the open-weight push.
Moonshot comeback: from post–DeepSeek R1 slump to K2 → K2.5 → K3 open-weight cadence.
| Scenario | Path | Why |
|---|---|---|
| Try now / coding agents | API or Kimi Code | Live since July 16; caching cuts cost |
| Post-7/27 fine-tune / residency | Self-host (64+ GPUs) | Needs full weights + compliance |
| Cost-sensitive | DeepSeek V4 Pro API | $3.48/M output |
| Long-horizon reasoning | Claude Fable 5 | GDPval / overall index lead |
| Wait for Ollama/GGUF | Track K2 follow-ons | Consumer quantizations lag the HF drop |
Sources: kimi.com/en/blog/kimi-k3, platform.kimi.ai, Artificial Analysis (July 16), VentureBeat, Northflank, r/LocalLLaMA, Hacker News.
July 27, 2026 on Hugging Face with a technical report. API shipped July 16.
Open weights under Modified MIT—not fully open source (no complete training stack/data release).
$3 / $0.30 cached / $15 per million tokens; ~$0.94 per task in AA testing.
No—~1.4 TB at 4-bit, 64+ accelerators recommended. Use the API.
Overall index: no (57.1 vs 59.9). Several coding/UI benches: yes. Cost per task: much lower.
Modified MIT—confirm exact terms in the Hugging Face LICENSE on July 27.
Open weights on July 27 do not magically shrink a 2.8T model onto your desk GPU. Most builders will consume K3 through API, Kimi Code, or OpenRouter; self-hosting remains an enterprise-scale bet. If your workflow also needs a real macOS GUI—Kimi Code agents, OpenClaw routing, Xcode signing dialogs SSH cannot click—buying hardware is expensive and idle nodes depreciate fast. VNCMac remote Mac rental gives you an on-demand VNC desktop to validate long-context coding and agent flows, then stop paying when the sprint ends. See Mac rental pricing or our July 17 Kimi K3 review for deeper architecture detail.