Moonshot AI's economical 256K-context version of Kimi K3 — the same flagship model with the window capped at 256,000 tokens, using roughly half the quota of the 1M model for everyday long-form work.
Last verified · 2026-07-29 · by Moe Ameen
Kimi K3-256k is a context variant of Kimi K3, Moonshot AI's flagship frontier model. It is not a separate model — it is the same K3 intelligence with the context window fixed at 256,000 tokens instead of the full one million. Moonshot exposes it as the model ID k3-256k in Kimi Code, selectable alongside the 1M k3, and positions it as the economical everyday driver: you keep K3's reasoning and native image understanding, and you spend markedly less on each run.
The reason it exists is cost. Moonshot's own documentation notes that the 1M-token k3 consumes roughly twice the quota of k3-256k, and recommends switching to the 256K version for everyday tasks that don't need the maximum window. 256,000 tokens is still enormous — enough to hold a book-length manuscript, a full content back-catalog, or a large batch of transcripts in a single pass — so for most drafting and editing work the cap is invisible while the savings are real. In Kimi Code's membership tiers, K3 at up to 256K unlocks at the Moderato level and above, while the full 1M window and the high-speed coding tier require Allegretto or higher. Kimi K3 itself began rolling out in mid-July 2026; API pricing for the model was listed around $3 per million input tokens and $15 per million output at launch.
Because it is K3 underneath, K3-256k is natively multimodal — it reads images and screenshots as first-class input — and it is strong at reasoning, code, and long-document work. But it is still a raw model: it outputs text, code, and analysis. It renders no captioned video, no branded image, no carousel, and it publishes to nothing. It is a good, cheap engine for producing and revising long-form writing — not a studio that turns that writing into finished, scheduled posts.
K3-256k earns its keep on the part of content work that is pure text: getting a long draft written and then editing it until it is right. Its 256K window is big enough to hold a full blog post, a webinar transcript, and your style notes at once, and because it costs about half the quota of the 1M model, you can iterate — rewrite the intro five times, tighten every section, cut the draft in half — without watching a meter. What you end up with is a clean, finished piece of writing. What you do not end up with is anything a follower ever sees: a vertical short, a face-locked avatar clip, a brand-exact carousel, a quote card, a scheduled post. That handoff is exactly where Kompozy starts.
Drop the polished long-form draft into Kompozy as a source and it becomes a whole week of media instead of one document. Kompozy clips and captions it into Persona Shorts and Clipped Shorts, lays the key points into brand-exact Carousels and Quote Graphics through HyperFrames, spins the argument into a Blog Article and an Email Newsletter, and writes the platform-native posts to carry it — every output held to one voice by your Persona Brief rather than reading like model output. Then it schedules and publishes the set across nine platforms plus email and blog from a single queue on Autopilot. You never operate K3-256k through Kompozy — Kompozy runs its own managed Claude and OpenAI models — so the clean split is: edit the long text cheaply in K3-256k, then let Kompozy turn one finished draft into the video, images, and posts that ship.
Kimi K3-256k is a context variant of Moonshot AI's flagship Kimi K3 model, with the context window fixed at 256,000 tokens instead of the full 1 million. It is the same K3 intelligence — reasoning, code, and native image understanding — offered as the model ID k3-256k in Kimi Code as an economical everyday option. Moonshot notes the 1M k3 uses roughly twice the quota of k3-256k.
It is the same model with a smaller context window. Full Kimi K3 can take up to a million tokens; k3-256k caps context at 256,000 tokens and, per Moonshot's docs, consumes about half the quota, which is why Moonshot recommends it for everyday tasks that don't need the maximum window. Intelligence and multimodal input are the same; only the context ceiling and cost differ.
For most work, yes. 256,000 tokens is roughly a book-length amount of text, enough to hold a long draft, a transcript, and your notes in one pass. You only need the 1M window for genuinely massive inputs — an entire archive at once. For drafting and editing a single long piece, K3-256k is the cost-efficient choice.
No. Like any raw model, it produces text, code, and analysis and reads images, but it renders no captioned video, branded graphics, or scheduled posts. To turn a K3-256k draft into finished, on-brand content across nine platforms plus blog and email, pair it with a content engine like Kompozy, which generates 18 formats and handles publishing.
In Kimi Code it is metered by membership quota rather than a separate per-token price, and it uses about half the quota of the 1M k3; access to K3 at up to 256K starts at the Moderato tier. The underlying Kimi K3 model listed API pricing around $3 per million input tokens and $15 per million output at launch. Confirm current quotas and pricing on Moonshot's own pages.