morph/kimi-k3-fast

morph/kimi-k3-fast is a frontier-tier language model from RouterPlus. morph/kimi-k3-fast is a proprietary model available exclusively through RouterPlus's API. The Kimi K3 family is RouterPlus's model series for this capability tier.

morph/kimi-k3-fast is priced at $6/1M input tokens and $22.5/1M output tokens. Output tokens are 3.8× more expensive than input tokens — this ratio reflects the sequential nature of autoregressive generation, which requires a separate forward pass per output token versus parallel processing of all input tokens simultaneously. At a typical usage pattern of 1,000 input tokens and 500 output tokens per call, morph/kimi-k3-fast costs approximately $17.25 per 1,000 API calls. Prompt caching reduces repeated input tokens to $0.6/1M — a 90% discount that compounds significantly for applications with long shared system prompts, multi-turn conversations, or document Q&A where the same context is reused across many queries.

Its 1.0M-token context window is among the largest available — sufficient for processing entire codebases, book-length documents, or hours of transcribed audio in a single API call. Maximum output length is 524K tokens — sufficient for long-form content generation, detailed code files, and extended reports.

morph/kimi-k3-fast is best suited to general language tasks. Supported capabilities include streaming token output for real-time UIs. When evaluating this model for a specific workload, the most important factors are: context window (does your input fit?), output price (how long are your generations?), and latency (is this interactive or batch?). The pricing table above shows how morph/kimi-k3-fast compares to similar models across these dimensions.

morph/kimi-k3-fast sits in the frontier tier — the highest-capability models available, used when quality is the primary constraint and cost is secondary. Unlike open-weights alternatives, morph/kimi-k3-fast is only available via RouterPlus's API — there is no self-hosted option, which simplifies deployment but creates vendor dependency. When comparing morph/kimi-k3-fast to alternatives, use the similar models section on this page to find models at comparable price points with different capability tradeoffs. The intelligence score (N/A/100) reflects aggregate benchmark performance — a useful proxy for general capability, though real-world performance varies significantly by task type. Always test with your specific prompts and use case before committing to a model for production.