How to Use Kimi K3 in Opencode, Claude Code, and Your Coding Agent
Blog post from Featherless
Moonshot’s Kimi K3 is an open-weight mixture-of-experts model with 2.8 trillion total parameters, roughly 104 billion active parameters per token, a native one-million-token context window, multimodal capabilities, and tool calling designed for agent workflows; Moonshot reports frontier-level benchmark performance, although some results use differing test harnesses. Because its approximately 1.56 TB weights and recommended 64-plus-accelerator deployment make local operation impractical, Featherless offers it through an OpenAI-compatible API under the model ID moonshotai/Kimi-K3, providing 256K context on its serverless Developer plan and up to one million tokens on dedicated infrastructure. The setup process for OpenCode, Claude Code via Claude Code Router, Cline, Roo Code, Aider, and other compatible agents mainly requires the Featherless base URL, an API key, model ID, and appropriate context-limit settings, while custom agent implementations must preserve reasoning and tool-call data across turns. The guide distinguishes pay-as-you-go serverless use for occasional or individual development from dedicated GPU deployments for sustained, high-concurrency agent workloads, arguing that reserved hardware can offer more predictable latency and lower costs at scale; listed serverless pricing is $2 per million input tokens, $0.30 per million cached tokens, and $10 per million output tokens. Although K3’s weights permit commercial use under a conditional license, its training data and training recipe are not public, and its coding performance is presented as competitive with leading proprietary models but dependent on the task and token usage.
No tracked trend matches for this post yet.
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.