Visual agents
Give an agent screenshots, charts, document pages, and tool results without flattening every visual into plain text first.
Independent tool overview
GLM-4.6V at a glance
GLM-4.6V is Z.ai's English-and-Chinese vision-language model family for documents, images, video, visual coding, and multimodal tool use.
Visit the official GLM-4.6V site ↗
- Developer
- Z.ai
- Inputs
- Text, images, video, and files
- Output
- Text
- Context window
- 128K tokens
- Languages
- English and Chinese
- Starting API price
- Free with Flash
Overview
What GLM-4.6V is
GLM-4.6V is a family of multimodal models from Z.ai. It accepts text, images, video, and files, returns text, and supports a 128K-token context window. Its distinguishing feature is native multimodal function calling: visual inputs and visual tool results can remain part of the model's reasoning and action loop.
The family includes the higher-performance GLM-4.6V, a lower-cost FlashX API option, and the free Flash variant. Z.ai also publishes open weights for the flagship and Flash models, so technically capable teams can evaluate self-hosting as well as the managed API.
Z.ai has since introduced newer vision models, including GLM-5V-Turbo, but GLM-4.6V remains documented, priced, and available. It is best evaluated as a cost-conscious model for visual agents and long multimodal inputs rather than assumed to be Z.ai's current flagship.
Use cases
Who GLM-4.6V is best for
The strongest fit depends on the job you need the product to complete, not the size of its feature list.
Document analysis
Analyze long, image-heavy reports, slides, tables, figures, and formulas in a shared multimodal context.
Screenshot-to-code
Generate and iteratively edit frontend code from screenshots or annotated rendered pages.
Video understanding
Summarize longer videos and reason about events or timestamps within the supported context and input limits.
Budget-sensitive prototypes
Start with the free Flash API or open weights before committing to a higher-performance managed model.
Capabilities
Core GLM-4.6V features
Native multimodal tool calling
Passes images and document pages into tools and interprets visual tool results inside an agent workflow.
128K multimodal context
Maintains text and visual information across long documents, slide decks, multiple files, or extended video inputs.
Thinking control
Supports a thinking parameter so developers can enable deeper reasoning for complex visual tasks or disable it where appropriate.
Document and chart understanding
Works directly with layouts, tables, figures, curves, and formulas instead of requiring a separate OCR-only pipeline.
Visual coding
Can recreate interfaces from screenshots and apply natural-language edits to selected areas of a rendered page.
OpenAI-compatible API pattern
Uses a chat-completions endpoint and supports the official Z.ai SDK as well as OpenAI-style client integrations.
Open weights
Official model repositories provide MIT-licensed flagship, FP8, and Flash variants for self-managed evaluation and deployment.
Process
How the GLM-4.6V workflow works
Step 1
Choose the variant
Use Flash for free experiments, FlashX for inexpensive low-latency calls, or GLM-4.6V when the higher-performance model is justified.
Step 2
Define the visual task
Specify the required output schema, acceptable evidence, image or video inputs, and whether tool use is allowed.
Step 3
Start with representative files
Test real screenshots, charts, scanned pages, mixed-language documents, and videos rather than relying only on benchmark examples.
Step 4
Control reasoning and output
Set thinking mode, streaming, token limits, and tool schemas deliberately to manage latency and cost.
Step 5
Validate grounding
Check extracted figures, bounding boxes, citations, timestamps, generated code, and tool arguments against the source material.
Step 6
Harden the deployment
Remove sensitive data where possible, restrict callable tools, log actions, add human approval for consequential steps, and regression-test upgrades.
Cost
GLM-4.6V pricing and free plan
Z.ai prices the managed GLM-4.6V family per million tokens. GLM-4.6V costs $0.30 for input and $0.90 for output; FlashX costs $0.04 for input and $0.40 for output; Flash is free. Self-hosted open weights have no model API fee but do require infrastructure and operations.
GLM-4.6V-Flash
Free
The lightweight free API variant for prototypes and lower-cost workloads.
- Free input
- Free output
- 128K context
- Native function calling
GLM-4.6V-FlashX
$0.04 input / $0.40 output
A faster, inexpensive managed option priced per one million tokens.
- $0.004 cached input
- Cached-input storage temporarily free
- 128K context
- English and Chinese
GLM-4.6V
$0.30 input / $0.90 output
The higher-performance managed model, priced per one million tokens.
- $0.05 cached input
- Cached-input storage temporarily free
- 128K context
- Maximum output up to 32K
Open weights
No API fee
Run an official MIT-licensed model variant on your own compatible infrastructure.
- Infrastructure not included
- Significant hardware needs for the flagship
- Deployment expertise required
- You manage security and uptime
Pricing checked . Check current pricing at the source ↗
Assessment
GLM-4.6V strengths and limitations
Where it stands out
- Native visual tool use supports richer agent workflows
- Long context accommodates substantial multimodal inputs
- Free and low-cost API variants make evaluation accessible
- Open weights provide a self-hosting path
- Strong fit for document, chart, screenshot, and frontend tasks
- English and Chinese support
- Clear token-based API pricing
What to consider
- GLM-4.6V is no longer Z.ai's newest vision-model generation
- Vendor benchmark claims do not guarantee accuracy on a specific workload
- Visual models can misread charts, small text, spatial relationships, or temporal details
- Long context does not ensure the model will retain or correctly use every input detail
- The flagship open-weight model has substantial storage, memory, and serving requirements
- Tool calling can amplify errors unless permissions and arguments are constrained
- Supported languages are narrower than some broadly multilingual competitors
- Sensitive documents and media require careful data-governance review
Compare
GLM-4.6V alternatives
The right alternative depends on the specific output, workflow, controls and budget your project requires.
Consumer
Gemini 3.1 Pro
Choose Gemini 3.1 Pro for a newer managed multimodal model with a broad Google developer ecosystem.
Explore Gemini 3.1 Pro →Consumer
Qwen3.5-Omni
Consider Qwen3.5-Omni when native audio as well as text, image, and video understanding is important.
Explore Qwen3.5-Omni →Consumer
Claude Sonnet 4.6
Choose Claude Sonnet 4.6 for mature visual analysis, coding, and agent workflows in Anthropic's platform.
Explore Claude Sonnet 4.6 →Questions
GLM-4.6V FAQs
What is GLM-4.6V?
It is Z.ai's vision-language model family for text, images, video, files, long-context analysis, and multimodal function calling.
Is GLM-4.6V still available?
Yes. Z.ai still documents and prices GLM-4.6V, FlashX, and Flash, although newer Z.ai vision models are also available.
How much does the GLM-4.6V API cost?
Per one million tokens, GLM-4.6V costs $0.30 for input and $0.90 for output. FlashX is $0.04 input and $0.40 output, while Flash is free.
Is GLM-4.6V open source?
Z.ai publishes official model weights and repositories under the MIT license. Review each repository and dependency before commercial deployment.
What can GLM-4.6V accept?
The documented API accepts text, images, video, and files and produces text output.
What is native multimodal function calling?
It means images, screenshots, and document pages can be passed directly into tool workflows, and the model can inspect visual results returned by those tools.
Should I use GLM-4.6V or Flash?
Start with free Flash to validate the workflow, test FlashX for lower-cost production calls, and move to GLM-4.6V only when measured quality gains justify its higher price.
Bottom line
Our GLM-4.6V verdict
GLM-4.6V remains a practical, attractively priced family for multimodal agents, document analysis, and screenshot-driven development. The free Flash tier and open weights lower the barrier to testing, but teams should benchmark it against newer models and independently validate every visual extraction and tool action.
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