MoonshotAI: Kimi K2 0905

Kimi K2 0905 is a text generation model from Moonshot AI, released on 4 September 2025 as the September update to Kimi K2 0711. It is a large-scale Mixture-of-Experts (MoE) language model with 1 trillion total parameters, and it sits in the text category on api14. If you are choosing a general purpose language model for a text pipeline, this is the model family and provider you would be evaluating here.

The model takes text as input and returns text as output, so it fits standard prompt and completion workflows rather than multimodal tasks. Its context window is 262,144 tokens, which is large enough to hold long documents, extended conversations or sizeable code files in a single request. The maximum output is 98,304 tokens, so long generations are possible within that window. Its knowledge cutoff is 31 December 2024, which is worth keeping in mind for questions about events or releases after that date.

Those capabilities point to a few practical uses. The long context suits summarisation and question answering over lengthy documents, contracts or research material, and it also supports repository-scale code assistance where several files need to be considered together. Because the model supports tools and structured outputs, it can be used for function calling and for producing responses that conform to a schema, which is useful in extraction and agent style workflows. The large output allowance helps when the task requires a long draft, a detailed report or an extended chain of reasoning in one response.

You call it through api14's OpenAI-compatible API using the model id "moonshotai/kimi-k2-0905". The supported request parameters are frequency_penalty, max_tokens, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k and top_p. That set covers sampling controls, determinism via seed, stopping conditions, structured output and tool use, so most OpenAI-style client code should work with only the model id changed.

One limit to note is that input and output are text only, so if your task depends on images or audio, a different model is needed. The knowledge cutoff of 31 December 2024 also means the model has no built in awareness of later events unless you supply that context in the prompt. For workloads where a smaller or faster model is sufficient, this one may be more than the task requires, but for long context text work with tool calling it is a reasonable candidate.