Z.ai Models

GLM-5.3-Prime is the high-speed variant of Z.ai's GLM-5.3, inheriting its full capabilities while delivering 1.5–2× higher output throughput through inference acceleration. It supports text input and output with a 1M-token context window and up to 128K output tokens, and is optimized for coding and agentic workloads, including long-horizon multi-turn agent orchestration, real-time conversation, and streaming code generation.

GLM-Image is an image generation model adopts a hybrid autoregressive + diffusion decoder architecture. In general image generation quality, GLM‑Image aligns with mainstream latent diffusion approaches, but it shows significant advantages in text-rendering and knowledge‑intensive generation scenarios. It performs especially well in tasks requiring precise semantic understanding and complex information expression, while maintaining strong capabilities in high‑fidelity and fine‑grained detail generation. In addition to text‑to‑image generation, GLM‑Image also supports a rich set of image‑to‑image tasks including image editing, style transfer, identity‑preserving generation, and multi‑subject consistency.

GLM-5 is Zai’s new-generation flagship foundation model, designed for Agentic Engineering, capable of providing reliable productivity in complex system engineering and long-range Agent tasks. In terms of Coding and Agent capabilities, GLM-5 has achieved state-of-the-art (SOTA) performance in open source, with its usability in real programming scenarios approaching that of Claude Opus 4.5.

GLM-4.6V-Flash is the free version of GLM-4.6V, representing a significant iteration in the GLM series for multimodal capabilities. It supports toggling reasoning modes, with a training-time context window expanded to 128k tokens. Achieving state-of-the-art (SOTA) visual understanding accuracy at its parameter scale, it is the first visual model to natively integrate Function Call capability into its architecture. This establishes a seamless pipeline from "visual perception" to "executable actions (Action)", offering a unified technical foundation for multimodal agents in real-world business scenarios.

As a 30B-class SOTA model, GLM-4.7-FlashX offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.

As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning, and tool collaboration, and has achieved leading performance among open-source models of the same size on several current public benchmark leaderboards.

Pricing: The model's official pricing is (GLM-4.7: Input $0.28 ~ $0.57, Cached Input $0.057~$0.11, Output $1.14~$2.27). Our platform is currently running a limited-time promotion, during which you will receive a discount on the official price. GLM-4.7 is Zhipu’s latest flagship model. Tailored for agentic coding scenarios, GLM-4.7 strengthens coding capabilities, long-horizon task planning, and tool collaboration, and delivers leading performance among open-source models on the latest leaderboards of multiple public benchmarks. Its general capabilities have also improved, with responses that are more concise and natural and writing that feels more immersive. When executing complex agent tasks and invoking tools, it follows instructions more reliably, while the visual quality of artifacts and agentic coding front ends—as well as long-horizon task completion efficiency—are further enhanced.

GLM-4.6V represents a significant evolution of the GLM series into the multimodal domain. It features a 128k-token training context window and sets a new state-of-the-art in visual understanding accuracy for its parameter scale. Pioneeringly, it is the first model to natively integrate tool-calling capabilities into its visual architecture, bridging the gap from visual perception to executable actions. This makes it a unified technical foundation for multimodal Agents in real-world business scenarios. Pricing: The model's official pricing is (GLM-4.6v: Input $0.3, Cached Input $0.05, Output $0.9). Our platform is currently running a limited-time promotion, during which you will receive a discount on the official price.

GLM-4.6V-FlashX is the the paid version, offering higher capacity and stability， representing a significant iteration in the GLM series for multimodal capabilities. It supports toggling reasoning modes, with a training-time context window expanded to 128k tokens. Achieving state-of-the-art (SOTA) visual understanding accuracy at its parameter scale, it is the first visual model to natively integrate Function Call capability into its architecture. This establishes a seamless pipeline from "visual perception" to "executable actions (Action)", offering a unified technical foundation for multimodal agents in real-world business scenarios.

GLM-4.6 is a flagship model from Zhishen with 355B total parameters and 32B active parameters. The model's context window has been expanded from 128K to 200K, enabling it to handle longer code and agent tasks. In programming capabilities, GLM-4.6's performance is comparable to Claude Sonnet 4 on public benchmarks and real-world programming tasks. The model supports tool calling during inference and features optimized search and tool-use performance within agent frameworks. Furthermore, enhancements have been made to its writing style, readability, role-playing, and cross-lingual task processing abilities.

Pricing: The model's official pricing is (GLM-4.6: Input $0.6, Cached Input $0.11, Output $2.2). Our platform is currently running a limited-time promotion, during which you will receive a discount on the official price.

GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly enhanced capabilities in reasoning, code generation, and agent alignment. It supports a hybrid inference mode with two options, a "thinking mode" designed for complex reasoning and tool use, and a "non-thinking mode" optimized for instant responses. Users can control the reasoning behaviour with the reasoning enabled boolean.

GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a more compact parameter size. GLM-4.5-Air also supports hybrid inference modes, offering a "thinking mode" for advanced reasoning and tool use, and a "non-thinking mode" for real-time interaction. Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs

GLM-5 Turbo is a new model from Z.ai designed for fast inference and strong performance in agent-driven environments such as OpenClaw scenarios. It is deeply optimized for real-world agent workflows involving long execution chains, with improved complex instruction decomposition, tool use, scheduled and persistent execution, and overall stability across extended tasks.

GLM-5V-Turbo is Zhipu’s first multimodal coding base model, designed for vision-based programming tasks. It can natively process multimodal inputs such as images, video, and text, and excels at long-horizon planning, complex programming, and action execution. It is deeply adapted to Agent workflows and can closely collaborate with Agents like Claude Code and OpenClaw to complete a full closed loop of “understanding the environment → planning actions → executing tasks.

GLM-5.1 is Zai’s new-generation flagship foundation model, designed for Agentic Engineering, capable of providing reliable productivity in complex system engineering and long-range Agent tasks. In terms of Coding and Agent capabilities, GLM-5 has achieved state-of-the-art (SOTA) performance in open source, with its usability in real programming scenarios approaching that of Claude Opus 4.5.

GLM-5.2 supports a larger context window and output length, with up to 1M context and 128K output tokens. It adds streaming output for tool calls via tool_stream=true, enabling real-time access to tool call arguments. Like the GLM-4.7 series, it supports deep thinking with thinking={ type: "enabled" }, where thinking is enforced once enabled, and introduces reasoning_effort to control reasoning intensity under chain-of-thought mode. It also delivers stronger coding performance and more advanced reasoning capabilities.

GLM-5.3 is Zhipu AI’s next-generation flagship text model, built on GLM-5.2 and enhanced through large-scale, long-horizon task post-training. It delivers an approximately 50% improvement in coding experience, autonomously handling complex project development, debugging, validation, and delivery. It also supports a 1-million-token context window, up to 128K-token outputs, tool calling, and MCP, with strong performance in cybersecurity tasks such as code review and vulnerability detection.

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

GLM-5.3-FlashX is a faster and smoother version of GLM-5.3-Flash, delivering inference speeds of up to 200 tokens/s. GLM-5.3-FlashX is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.