Open Bigmodel Cn Zhipu AI GLM API
66
AI ReadinessAI-Aware (B)66/100
Official vendor OpenAPI document · agent-readyAI/MLLanguage Modelsbearer13 EndpointsREST
For Agents
Create chat completions, embeddings, and image and video generations with Zhipu's GLM models, poll async tasks, manage files, and run batch inference jobs via an OpenAI-compatible interface.
Use for: Generate a chat completion with a GLM model, Create embeddings for a set of documents, Generate an image from a text prompt, Produce a short video from an image
Not supported: Does not handle model fine-tuning, vector storage, or speech transcription. Use for GLM text, image, and video generation only.
The Zhipu AI GLM API provides access to Zhipu's GLM family of large language models through an OpenAI-compatible interface. It creates chat completions, text embeddings, image generations, and video generations, polls long-running generation tasks by task id, manages uploaded files, and runs batch processing jobs. Developers use it to add GLM-powered reasoning, multimodal generation, and bulk inference to their applications.
Install Jentic One Beta
Connect the Zhipu AI GLM API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Zhipu AI GLM API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fopen.bigmodel.cn%2Fopen-bigmodel" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fopen.bigmodel.cn%2Fopen-bigmodel" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Zhipu AI GLM API.
Create chat completions with Zhipu's GLM models
Generate text embeddings for semantic search and retrieval
Generate images from a text prompt
Generate video from text or an image prompt
Poll a long-running generation task by its task id
Upload and manage files and run batch inference jobs
Use Cases
Patterns agents use Zhipu AI GLM API for, with concrete tasks.
★ AI Assistant on GLM
An AI agent connected through Jentic answers and reasons using Zhipu's GLM models by calling the chat completion operation, so a product can run on GLM without the developer wiring the Zhipu auth and request format by hand. The OpenAI-compatible shape means prompts and tool calls map across with minimal change.
Send a multi-turn conversation to a GLM chat model and return the assistant's reply
Multimodal Generation
A content tool generates visuals by sending a text prompt to the image generation operation and a text or image prompt to the video generation operation, polling each long task by its task id until the asset is ready. One provider covers text, image, and video output.
Generate an image from a prompt, then poll the task id until the image URL is returned
Batch Inference
A data pipeline runs large sets of prompts cost-effectively by uploading an input file and submitting a batch job, then collecting results when the job completes. Files and batches are tracked by id, so a pipeline can fire many jobs and reconcile outputs asynchronously.
Upload a prompt file, create a batch job over it, and retrieve the results once the job completes
Key Endpoints
13 endpoints — the zhipu ai glm api provides access to zhipu's glm family of large language models through an openai-compatible interface.
METHOD
PATH
DESCRIPTION
POST
/chat/completions
Create a chat completion
POST
/embeddings
Create text embeddings
POST
/images/generations
Generate images from text
POST
/videos/generations
Generate video from text or image
GET
/async-result/{task_id}
Get an async task result
POST
/batches
Create a batch processing job
GET
/files
List uploaded files
POST
/chat/completions
Create a chat completion
POST
/embeddings
Create text embeddings
POST
/images/generations
Generate images from text
POST
/videos/generations
Generate video from text or image
GET
/async-result/{task_id}
Get an async task result
POST
/batches
Create a batch processing job
GET
/files
List uploaded files
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
Z
Zhipu AI GLM API
- AI-Aware (B)66/100
87
Foundational Compliance63
Developer Experience & Jentic Compatibility49
AI-Readiness & Agent Experience94
Agent Usability60
Security71
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.2
Show dimension breakdown
87
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: ASignals: 4
98%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
100%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
50%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
63
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: BSignals: 4
2%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
50%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
49
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: D+Signals: 4
43%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
54%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
60
Security
Trust, risk posture, and security compliance.
Grade: B-Signals: 1
60%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
71
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: A-Signals: 1
71%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring the Zhipu GLM API by hand means handling its bearer token, polling async generation tasks, and tracking file and batch job state yourself. Through Jentic you install once, import Zhipu GLM from the API Directory, store the token once, and your agent calls it.
Permission scoping
A rule can give your agent just the chat and embedding operations and leave file deletion, image, video, or batch operations out unless you add them. You choose which operations it may call.
Credential isolation
Your Zhipu GLM API token is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'generate a chat completion' or 'create an image', and Jentic returns the matching Zhipu GLM operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Zhipu AI GLM API through Jentic.
What authentication does the Zhipu AI GLM API use?
The Zhipu AI GLM API authenticates with a bearer token in the Authorization header, per its OpenAPI spec, following the OpenAI-compatible convention. Through Jentic that token is held encrypted by your own Jentic One instance and injected at call time, so it never appears in the agent's prompt or logs.
Can I generate images and video with the Zhipu AI GLM API?
Yes. The image generation operation turns a text prompt into images, and the video generation operation produces video from text or an image. Both can run as long tasks you poll by task id until the output is ready.
What are the rate limits for the Zhipu AI GLM API?
The OpenAPI spec does not define rate limits for the Zhipu AI GLM API. Zhipu sets per-account limits that vary by model, documented at https://open.bigmodel.cn/dev/api, so check there before scaling up.
Can I limit what my agent is allowed to do with the Zhipu AI GLM API?
Yes. Write a rule that allows only the chat and embedding operations, so the agent reasons and embeds while file deletion, image, video, and batch operations stay out of its reach unless you add them. Every call the agent makes is logged.
How do I create a chat completion with the Zhipu AI GLM API through Jentic?
Search by intent in Jentic with a query like 'generate a GLM chat completion', add the Zhipu AI GLM API from the Jentic API Directory, and your agent sends the conversation to a GLM model and reads the reply. To run it on your own infrastructure, install Jentic One from its GitHub repo.
GET STARTED