Z.ai
on Orq.ai
Access Z.ai’s GLM models through Orq.ai for reasoning, coding, multilingual, multimodal, and other AI workloads through one API.
Capabilities:
Chat
Reasoning
Code
Vision
Models Supported:
glm-5.2
glm-5.1
glm-5v-turbo
glm-4.7-flashx
glm-5-turbo
glm-4.5-air
glm-4.5-flash
glm-4.6v
cogView-4-250304
glm-4.5
...
Provider HQ:
Beijing, China
Access Z.ai through Orq.ai’s AI Router
Z.ai provides the GLM family of models and APIs for reasoning, coding, multilingual applications, multimodal workloads, and tool-based AI systems. Its platform also supports specialized capabilities such as vision, OCR, media generation, speech, and agent workflows.
Z.ai models available on Orq.ai
Compare the Z.ai models currently available through Orq.ai, including their supported capabilities, context windows, pricing, and regional availability.
Model
Type
Context
Input / 1M
Output / 1M
glm-5.2
chat
Reasoning
1M
$1.40
$4.40
glm-5.1
chat
200K
$1.40
$4.40
glm-5v-turbo
chat
Reasoning
Vision
Video
200K
$1.20
$4.00
Why use Z.ai through Orq.ai?
Using Z.ai through Orq.ai lets teams combine multilingual reasoning, coding, multimodal, and specialized AI capabilities with a wider model stack without maintaining separate routing, evaluation, observability, and cost-control logic for each provider.
Capability | Provider | Direct | Through Orq.ai |
|---|---|---|---|
Chat & reasoning | Z.ai GLM models | Call supported GLM models directly for multilingual chat, reasoning, generation, and assistant workloads. | Route Z.ai models through Orq.ai while applying routing, tracing, evals, budgets, and governance controls around each request. |
Coding | Z.ai GLM models | Use supported models for code generation, debugging, refactoring, and agentic coding workflows. | Route coding workloads through Orq.ai, compare Z.ai with other providers, and monitor cost, latency, and quality from a shared control layer. |
Vision & tools | Supported Z.ai capabilities | Use supported APIs directly for vision, OCR, media generation, speech, agents, and other specialized workloads. | Incorporate supported Z.ai capabilities into broader AI workflows while keeping observability, evaluations, and governance in the same platform. |
Pricing
Z.ai pricing varies by model, capability, usage type, and billing configuration.
Different workloads may use different billing structures. Language-model inference can use token-based pricing, while image, video, speech, OCR, agent, and other capabilities may use their own usage units.
You can connect supported Z.ai credentials to Orq.ai or use other available access options depending on your workspace configuration. Check Orq.ai and your Z.ai setup for current rates, quotas, and billing details.
Compatible frameworks and tools
Z.ai supports API interfaces that can be used with common model-development clients, while Orq.ai provides a shared routing layer for supported integrations.
Supported Z.ai models and capabilities can be incorporated into Orq.ai workflows depending on the model, endpoint, and workspace configuration.
Check the Orq.ai integration documentation for the latest setup options and compatibility information for Z.ai.
FAQs
Do I need a separate Z.ai account to use Z.ai through Orq.ai?
You can connect supported Z.ai credentials to Orq.ai or use other available access options depending on your workspace, plan, and region. Orq.ai provides a shared layer for routing, observability, evaluations, and cost controls around that usage.
Can I route only some workflows to Z.ai and others to different providers?
Yes. Orq.ai lets you route different workloads to different providers, so you can use Z.ai where multilingual reasoning, coding, multimodal capabilities, or cost characteristics fit the workload while routing other requests elsewhere.
Does using Z.ai through Orq.ai add latency?
Orq.ai adds a routing layer between your application and the provider. Teams can monitor end-to-end latency and use routing, caching, and provider controls where appropriate to manage performance.
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