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Kimi K3-256K

Kimi K3-256K is a coding-oriented language model surfaced through the Kimi Code product line, with its canonical documentation hosted at the official kimi.com/code/docs page. Independent developer coverage frames it as a deliberate engineering trade-off: rather than pushing every coding task through the largest available context, K3-256K offers a 256K context window positioned as a high-efficiency alternative to a larger K3 1M variant. The design intent is to keep high-quality outputs for routine work like refactors, unit-test generation, and boilerplate creation while reducing token consumption relative to over-sized context budgets.

Practical fit centers on CI/CD pipelines, IDE assistants, and other developer workflows where most prompts and supporting code do not need mega-context ingestion. The model has attracted substantial community attention, with a Hacker News thread linking to its official docs page accumulating several hundred points and a long comment thread discussing cost and context-length pricing tiers above the 256K mark. For teams that want a coding-tuned model sized to everyday engineering tasks rather than repository-wide reasoning, K3-256K represents a measured middle ground in the K3 family.

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Quick Info

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Provider
Kimi For Coding
Model key
k3-256k
Release date
Jul 16, 2026
Last updated
Jul 16, 2026
Input modalities
Output modalities
Capabilities

Cost

A provider subscription or plan supersedes token-based pricing for this model.

Limits

Output tokens
131,072 tokens
Context window
262,144 tokens

Latest news about Kimi K3-256K

Kimi For Coding

Coverage

A TechFlow Intel daily roundup from July 30, 2026 explicitly notes that Kimi released a 256K context, code-specific model called K3-256K, with Moonshot AI positioned as entering the code-model category directly against Claude Code and GPT-4o for long-context programming scenarios. The item frames this as part of an acc The roundup does not link to a Kimi or Moonshot announcement, model card, benchmark figures, pricing, or API details, and the surrounding Hacker News discussion reportedly questioned benchmark credibility and actual code completion experience. As an aggregator mention published about a month before the current date, it

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