Z.ai: GLM 5.1

Z.ai: GLM 5.1 is a text model from Z.ai, listed under the model id z-ai/glm-5.1. It is positioned by its provider as a step forward in coding capability, with emphasis on long-horizon tasks. Z.ai describes it as able to work independently and continuously on tasks, in contrast to earlier models built around minute-level interactions.

The model takes text input and returns text output. It has a context window of 204,800 tokens and a maximum output of 128,000 tokens. Alongside standard sampling controls, it exposes a reasoning parameter and an include_reasoning option, so a request can ask for reasoning content in the response. It also supports structured outputs and response_format, which lets you constrain generation to a schema rather than parsing free text. Tool use is supported through tools and tool_choice. Other supported parameters include frequency_penalty, presence_penalty, repetition_penalty, temperature, top_p, top_k, min_p, seed, stop, logit_bias, logprobs, top_logprobs, and max_tokens.

Those capabilities point to a few practical uses. The large context window and long maximum output suit work that spans many files or long documents, such as repository-level code tasks, multi-step refactors, and extended agent runs where the model keeps going without a human turn at every step. The reasoning controls help on problems that benefit from a visible intermediate trace. Structured outputs fit extraction and classification pipelines where the downstream code expects a fixed shape. Tool calling makes it usable as the decision layer in an agent that reads files, runs queries, or calls internal services.

You call it through api14's OpenAI-compatible API using the model id z-ai/glm-5.1. Because the interface follows the OpenAI chat completions shape, existing OpenAI SDKs and clients work with a base URL change, and requests carry the usual messages array plus any of the parameters listed above.

There is no stated restriction on input or output beyond text, so if you need image, audio, or other modalities, a different model would be the better fit. Likewise, the supported parameter list defines what the endpoint accepts, so anything outside it should not be expected to take effect.