GLM-5 is a text-based foundation model from Z.AI, designed for complex system engineering and long-range agent tasks. Z.AI describes it as a model for planning and carrying out multi-step work, including coding and tool use. Its documentation lists a 200K-token context length and up to 128K output tokens. These are published model specifications; a provider may expose different limits or features. (Z.AI model documentation)
GLM-5 is a specific model name, not a generic API standard. Z.AI describes GLM-5.1 as a later flagship model. Do not assume that specifications or API instructions for GLM-5.1—or for the separately documented multimodal model GLM-5V-Turbo—also apply to GLM-5. (Z.AI GLM-5.1 documentation; Z.AI GLM-5V-Turbo documentation)
What is GLM-5 designed to do?
Z.AI positions GLM-5 for “Agentic Engineering”: complex systems work and longer-running tasks involving multiple steps. Its documentation lists coding, agent tasks with tool invocation, structured output, text extraction, translation, and long-form writing among its use cases. These are vendor descriptions of intended capabilities, not guarantees of performance on a particular task or provider. (Z.AI model documentation)
As one benchmark example, Z.AI reports that GLM-5 finished Vending Bench 2 with a $4,432 account balance. The benchmark asks a model to run a simulated vending-machine business over a one-year horizon, with the ending balance used as its score. This result speaks to that evaluation; it does not show that the model can reliably manage a real business or production system. (Z.AI GLM-5 release post; Vending-Bench 2 description)
A reasonable workload to evaluate: multi-step coding, project planning, or tasks where the model must use tools and maintain a goal across several stages. A key limitation when interpreting claims: vendor capability descriptions and benchmark results do not establish how reliably the model will handle your own data, workflow, or failure cases. Test those directly before relying on it.
GLM-5 vs. GLM-5.1 and GLM-5V-Turbo
These are distinct model names; do not treat their specifications or API instructions as interchangeable.
- GLM-5 is the model described in this guide.
Z.AI’s release post reports 744 billion total parameters and 40 billion active parameters, and says the weights were released under the MIT License. (Z.AIGLM-5 release post) - GLM-5.1 is a later model.
Z.AIdescribes it separately and lists its own capabilities and limits. Those details apply to GLM-5.1, not GLM-5. (Z.AIGLM-5.1 documentation) - GLM-5V-Turbo is a separately named multimodal coding model.
Z.AI’s documentation for it describes image, video, text, and file inputs; those are not specifications for GLM-5. (Z.AIGLM-5V-Turbo documentation)
Some third-party coverage rounds GLM-5’s parameter count to about 745 billion. Z.AI’s release post gives 744 billion total and 40 billion active parameters; for technical or commercial decisions, prefer the official model-specific information over rounded secondary figures. (Z.AI GLM-5 release post; WaveSpeed GLM-5 article)
Accessing GLM-5 through a production API
Z.AI’s GLM-5 release post says the model is available on its developer platform. Z.AI documents a general chat-completions route at https://api.z.ai/api/paas/v4/chat/completions, but the current example returned in that documentation uses the model ID glm-5.3, not glm-5. This guide has not verified a current GLM-5-specific request ID or confirmed that GLM-5 is currently enabled for a particular account. Do not infer those details from the general endpoint alone. (Z.AI GLM-5 release post; Z.AI chat-completions documentation)
Before launch, verify these details with the provider you will actually use:
- Exact model ID and version: confirm that requests target GLM-5—not GLM-5.1 or GLM-5V-Turbo—and that the model is available to your account.
- Endpoint and authentication: confirm the applicable base URL, route, API-key type, and required headers.
Z.AInotes that keys for different products may not be interchangeable. (Z.AIAPI introduction) - Request and response behavior: check supported message formats, tool calling, structured output, streaming, errors, and token-usage fields.
- Operational terms: confirm context and output limits, rate limits, availability terms, and data-handling conditions.
- Price: check the provider’s current GLM-5 rates and billing units. Do not assume a third-party listing or a rate for a newer model applies to GLM-5.
The GLM-5-specific request identifier and current production terms should be confirmed with your selected provider. Do not copy an example for GLM-5.1, GLM-5.3, or GLM-5V-Turbo and assume it will work for GLM-5.
How to decide whether GLM-5 fits your workload
Run a small evaluation using representative tasks before choosing GLM-5 for production. Include typical inputs, difficult edge cases, and expected tool use. Score outputs against your requirements for correctness, completeness, format adherence, and safe failure behavior; also record latency and usage cost with the provider and settings you intend to deploy.
Compare those results with your current model or a relevant alternative. GLM-5’s stated focus makes it a candidate to test for complex, multi-step engineering work, but the right choice depends on measured results and provider terms—not the model description alone. Confirm current availability, pricing, and limits before budgeting or rollout.
Sources
GLM-5 - Overview - Z.AI Developer Documentation
GLM-5: From Vibe Coding to Agentic Engineering - Z.AI
GLM-5.1 - Overview - Z.AI Developer Documentation
GLM-5V-Turbo - Overview - Z.AI Developer Documentation
What Is GLM-5? Architecture, Speed & API Access - WaveSpeed