Z.ai: GLM Latest

Z.ai: GLM Latest is a text model from Z.ai, published under the model id ~z-ai/glm-latest. The name reflects how the endpoint behaves: it always redirects to the latest GLM model from Z.ai, so you are not pinning a specific version but pointing at whatever the current GLM release is. That makes it a reasonable default when you want the newest GLM behaviour without tracking version numbers yourself, though it also means the underlying model can change over time.

The model takes text in and returns text out. It has a context window of 1,048,576 tokens and a maximum output of 943,718 tokens, so both very long inputs and very long generations are possible within those bounds. It supports reasoning, which you can steer with the reasoning and reasoning_effort parameters, and it can report reasoning content when you set include_reasoning. Structured outputs and response_format are supported, as are tools, tool_choice and parallel_tool_calls, so function calling and schema-constrained generation are both available.

Those capabilities point to a few practical uses. The large context suits long document work: summarising, extracting structured data from, or answering questions over lengthy files and codebases in a single request. Tool calling and structured outputs fit agent-style workflows and pipelines where the model must return machine-readable results or invoke external functions. Reasoning support helps on tasks that benefit from step-by-step analysis, and the large output ceiling is useful when you need a long generated artefact rather than a short answer.

You call it through api14's OpenAI-compatible API using the model id ~z-ai/glm-latest, so existing OpenAI SDKs and clients work with a change of base URL and model name. The request parameters it accepts are frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, parallel_tool_calls, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs and top_p. Sampling controls, penalties, seeding, stop sequences, log probabilities and tool configuration are therefore all available to tune behaviour per request.

One thing to keep in mind is that the endpoint tracks the latest GLM model rather than a fixed version, so behaviour can shift when Z.ai updates it; if you need reproducible outputs across time, a pinned model may suit you better. Input and output are text only, so image or audio work would need a different model. Within those bounds, the combination of a very large context, large output limit, reasoning controls and tool support covers a wide range of text workloads.