GLM 5
Neural Network
GLM 5 is Z.ai's flagship open model used for coding, system design, and agentic tasks.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GLM 5?
GLM 5 is Z.ai's flagship open model designed for complex system design and long agentic scenarios. Targeted at experienced developers, it handles large-scale programming tasks at a production-ready level comparable to leading market models. Via BotHub, GLM 5 is accessible without a VPN or foreign card, with pay-as-you-go billing in rubles for non-expiring tokens. Compare answers from over 250 neural networks in one window, and use the unified OpenAI-compatible API to switch models without rewriting integrations; data is protected by AES-GCM encryption. Teams get access to contracts, invoices, EDI, and an admin panel with limits. Useful for designing service architecture, reviewing large codebases, building agents for multi-step engineering tasks, refactoring legacy code, or integrating the model into your product via API.Frequently asked questions about GLM 5
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
This is a Z.ai text model with reasoning and tool calling. It is suitable for coding, analyzing large documents, analytics, and STEM tasks. It has a 204,800 token context window and accepts images and documents, making it convenient for mixed scenarios.
Up to 128,000 tokens in a single response, which is dozens of pages of text. Enough for a large technical document, extensive refactoring, or detailed analysis. If the response hits the limit, ask it to continue: the 204,800 token context allows for maintaining the entire dialogue.
Yes, the reasoning mode is confirmed: the model builds a chain of steps before answering. This is noticeable in tasks involving math, logic, code debugging, and long documents where details matter. Reasoning also consumes tokens, but the answers are more accurate.
Yes. GLM 5 supports function calling and structured JSON output, making it easy to integrate into agents, chatbots, and pipelines with external services. In BotHub, access is provided via a unified OpenAI-compatible API: you can switch models without rewriting your integration.
Images and documents — yes: according to our data, the model accepts them as input, so you can ask it to analyze a screenshot, diagram, table, or PDF. We have no information regarding audio and video, so for such files, it is better to choose a model where this capability is specified.
We do not have specific data on languages, so we cannot make any promises here — it is easier to test it with your own task. In BotHub, this is quick: the model opens without a VPN or foreign card, payment is in rubles on a pay-as-you-go basis, and you can compare answers from other models side-by-side.