GLM 5V Turbo
GLM 5V Turbo is Z.AI's vision-enabled turbo model released April 1, 2026. It turns screenshots and designs into code, debugs visually, and operates GUIs autonomously, combining GLM-5's agentic capabilities with multimodal vision input at a compact parameter size.
View API reference- Input and output price
- Input $1.20, Output $4, Per 1M tokens
- 24h uptime
- Loading AI Gateway uptime
import { streamText } from 'ai'
const result = streamText({ model: 'zai/glm-5v-turbo', prompt: 'Why is the sky blue?'})Copy link to headingPlayground
Try out GLM 5V Turbo by Z.AI. Usage is billed to your team at API rates. Free users (those who haven't made a payment) get $5 of credits every 30 days.
GLM 5V Turbo
Copy link to headingProviders
Route requests across multiple providers. Copy a provider slug to set your preference. Visit the docs for more info. Using a provider means you agree to their terms, listed under Legal.
| Provider |
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Copy link to headingUptime24 hours
Direct request success rate on AI Gateway and per-provider. Visit the docs for more info.
Copy link to headingThroughput24 hours
P50 throughput on live AI Gateway traffic, in tokens per second (TPS). Visit the docs for more info.
Copy link to headingLatency24 hours
P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds. View the docs for more info.
Getting started
Call GLM 5V Turbo through AI Gateway with the AI SDK generateText and streamText functions, or through the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs by changing the base URL. AI Gateway authenticates the request and routes it to an available provider.
Install the AI SDK (pnpm add ai dotenv), create an API key from the API Keys page, and set it as AI_GATEWAY_API_KEY in your environment. Full setup is covered in the text generation quickstart.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'zai/glm-5v-turbo', prompt: 'Why is the sky blue?', });
console.log(result.text);}
main().catch(console.error);Top-level parameters
The same GLM 5V Turbo request in each API format AI Gateway supports.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'zai/glm-5v-turbo', system: 'You are a concise technical assistant.', prompt: 'Summarize the tradeoffs between static generation and SSR.', maxOutputTokens: 1024, });
console.log(result.text);}
main().catch(console.error);Standard parameters like prompt, messages, temperature, and tools work as documented in the AI SDK docs. These are the parameters with model-specific behavior.
| Parameter | Type | Required | Description |
|---|---|---|---|
model | string | Yes | Model ID in the form creator/model, e.g. zai/glm-5v-turbo. AI Gateway routes the request to an available provider. |
maxOutputTokens | number | No | Hard cap on generated tokens. GLM 5V Turbo supports up to 128,000 output tokens. Reasoning tokens count toward this limit. |
reasoning | 'provider-default' | 'none' | 'minimal' | 'low' | 'medium' | 'high' | 'xhigh' | No | Provider-agnostic reasoning effort, available in AI SDK 7 or later. Maps to the provider’s native reasoning configuration; reasoning settings under providerOptions take precedence when both are set. See the Reasoning section below. |
providerOptions | Record<string, JSONValue> | No | AI Gateway routing options under gateway, plus any provider-native options under the provider’s own namespace — see the table below. |
Input limits
| Input | Formats | Sources | Max count | Max size | Limits |
|---|---|---|---|---|---|
| Text | — | — | — | — | Prompt and response share the 200K-token context window |
| Image | — | URL, base64, Uint8Array | — | — | Sent as image parts in messages; counts as input tokens |
| — | URL, base64, Uint8Array | — | — | Sent as file parts in messages; counts as input tokens |
Provider options
Set AI Gateway routing options under providerOptions.gateway. For provider-specific options, pass them under the provider’s namespace as documented by the AI SDK.
Learn more in the AI SDK provider docs.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'zai/glm-5v-turbo', prompt: 'Why is the sky blue?', providerOptions: { gateway: { only: ['zai'], }, }, });
console.log(result.text);}
main().catch(console.error);These AI Gateway routing options apply to every model. Provider-specific options pass through under the provider’s own namespace (for example providerOptions.anthropic) exactly as documented by the AI SDK.
| Parameter | Type | Required | Description |
|---|---|---|---|
providerOptions.gateway.only | string[] | No | Restrict routing to these provider slugs. Requests fail over only within the listed providers. |
providerOptions.gateway.order | string[] | No | Preferred provider order. Listed providers are tried first; unlisted providers remain available as fallbacks. |
providerOptions.gateway.sort | 'cost' | 'ttft' | 'tps' | No | Rank candidate providers by price, time to first token, or tokens per second instead of the default routing order. |
providerOptions.gateway.zeroDataRetention | boolean | No | Route only to providers with a zero-data-retention policy for this model. |
Routing across providers
AI Gateway serves the same model through multiple providers and fails over automatically. order expresses a preference while keeping every provider eligible; only is a hard allowlist — if none of the listed providers are available the request fails instead of falling back.
Options under a provider's own namespace (for example providerOptions.anthropic) are forwarded to that provider with the request. Providers ignore option namespaces that don't apply to them, so it is safe to set provider options alongside gateway routing options.
Reasoning
AI Gateway bridges reasoning across every API format. The AI SDK exposes a provider-agnostic top-level reasoning level (none, minimal, low, medium, high, or xhigh); the Chat Completions and Responses formats take the same effort under reasoning.effort; and the Anthropic Messages format uses a native thinking token budget. Whichever you send, the gateway maps it to the target model’s native configuration, converting between effort levels and token budgets as needed. Reasoning-related settings under providerOptions take full precedence over the top-level reasoning value and are never merged. Reasoning tokens typically count toward your output-token usage, though how they’re reported and billed varies by provider.
Learn more in the AI Gateway reasoning guide.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'zai/glm-5v-turbo', prompt: 'Explain the Monty Hall problem step by step.', reasoning: 'high', });
console.log(result.text);}
main().catch(console.error);Image input
Send images alongside text as message parts. Images count as input tokens.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'zai/glm-5v-turbo', messages: [ { role: 'user', content: [ { type: 'text', text: 'Describe this image.' }, { type: 'image', image: 'https://example.com/photo.jpg' }, ], }, ], });
console.log(result.text);}
main().catch(console.error);PDF input
Attach PDFs as file parts. Their contents count as input tokens.
import { generateText } from 'ai';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'zai/glm-5v-turbo', messages: [ { role: 'user', content: [ { type: 'text', text: 'Summarize this document.' }, { type: 'file', mediaType: 'application/pdf', data: 'https://example.com/document.pdf', }, ], }, ], });
console.log(result.text);}
main().catch(console.error);Tool calling
Expose tools the model can call. Define each tool’s inputs with a Zod schema.
import { generateText, tool } from 'ai';import { z } from 'zod';import 'dotenv/config';
async function main() { const result = await generateText({ model: 'zai/glm-5v-turbo', prompt: 'What is the weather in San Francisco?', tools: { getWeather: tool({ description: 'Get the current weather for a location', inputSchema: z.object({ location: z.string() }), execute: async ({ location }) => ({ location, temperatureC: 18 }), }), }, });
console.log(result.text);}
main().catch(console.error);Copy link to headingAbout GLM 5V Turbo
GLM 5V Turbo was released April 1, 2026 as the vision-enabled turbo variant in Z.AI's GLM-5 generation. It combines GLM-5's agentic capabilities with multimodal vision input, purpose-built for workflows where visual understanding drives code generation and UI interaction.
The model focuses on design-to-code generation. Given a screenshot or design mockup, GLM 5V Turbo produces responsive components that match the original layout. It can debug visually by examining screenshots of rendered output and identifying discrepancies, then generating fixes. The model also navigates real GUI environments autonomously, reading screen elements and performing actions without manual scripting.
Despite these multimodal capabilities, GLM 5V Turbo operates at a smaller parameter size than comparable vision-language models. This translates to faster inference and lower cost per request, making high-volume visual coding workflows economically viable. Through AI Gateway, it's accessible via the same unified API with built-in observability and provider routing.
Copy link to headingWhat To Consider When Choosing a Provider
- Configuration: GLM 5V Turbo converts visual designs to code. For best results, provide clean screenshots at sufficient resolution and specify the target framework (React, HTML/CSS, etc.) in your prompt.
- Configuration: You can use GLM 5V Turbo in an iterative loop: render code, screenshot the result, feed it back to the model for corrections. This workflow leverages both vision and coding capabilities.
- Configuration: The compact parameter size means faster inference, but the most complex visual reasoning tasks may benefit from the full GLM-4.6V (106B). Benchmark on your specific use cases.
- Zero Data Retention: Zero Data Retention is offered on a per-provider and model basis. See the documentation for details.
- Authentication: AI Gateway authenticates requests using an API key or OIDC token. You do not need to manage provider credentials directly.
Copy link to headingWhen to Use GLM 5V Turbo
Best for
- Design-to-code generation: Screenshots and mockups convert into responsive React components, HTML, and CSS
- Visual debugging: The model examines rendered output, identifies layout issues, and generates fixes
- GUI automation: Real screen environments navigated autonomously for testing and interaction workflows
- Agentic visual coding pipelines: Image understanding combined with autonomous code planning and iteration
- High-volume visual processing: The compact parameter size keeps inference fast and cost-effective
Consider alternatives when
- Maximum visual reasoning depth: GLM-4.6V (106B) provides the largest vision-language model in the lineup without speed constraints
- Text-only workloads: GLM-5-Turbo offers the same generation's speed without vision overhead
- Simple captioning or classification: A lighter vision model may be more cost-effective for basic image tasks
- Deepest text reasoning: The full GLM-5 text-only variant provides multiple thinking modes without vision input
Copy link to headingConclusion
GLM 5V Turbo bridges vision and code generation in a fast, compact package. For teams building design-to-code pipelines, visual debugging loops, or autonomous GUI agents, it delivers the GLM-5 generation's agentic capabilities with multimodal input at a practical speed and cost profile.
Copy link to headingFrequently Asked Questions
What can GLM 5V Turbo do with screenshots?
It converts screenshots and design mockups into responsive code, identifies visual bugs in rendered output, and navigates GUI environments by reading screen elements and performing actions.
How does GLM 5V Turbo compare to GLM-4.6V?
GLM 5V Turbo is a newer, compact vision model focused on coding and GUI tasks. GLM-4.6V is a larger 106B parameter model with broader vision-language capabilities including native multimodal function calling and interleaved image-text generation.
Does GLM 5V Turbo support design-to-code generation?
Yes. It's specifically built for this workflow. Provide a screenshot or design mockup and specify the target framework. The model generates matching responsive components.
What is the context window for GLM 5V Turbo?
200K tokens.
How do I authenticate with GLM 5V Turbo through AI Gateway?
AI Gateway provides a unified API key. No separate Z.AI account is needed. Use the
glm-5v-turbomodel identifier to route requests. BYOK is also supported.Can GLM 5V Turbo operate GUIs autonomously?
Yes. It reads screen elements, interprets visual context, and performs navigation actions in real GUI environments. This makes it useful for automated testing and UI interaction workflows.
What is the pricing for GLM 5V Turbo?
Check the pricing panel on this page for today's numbers. AI Gateway tracks rates across every provider that serves GLM 5V Turbo.