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⚡ Run with API

Visual understanding, information extraction, and tool calling.

Pricing: Input 118.8 credits / 1M tokens (≈ $0.59), Output 356.4 credits / 1M tokens (≈ $1.78).

Prices updated

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This demo page does not include the full memory features of the client. For the complete experience, please use the client or the CLI.

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README
Complete guide to using GLM-4.5V

GLM-4.5V API

Call GLM-4.5V on ModelFold with model id glm-4-5v.

What this model is for

Context window

65,536 tokens of context for longer conversations, document analysis, and code.

Visual understanding

Accepts text and images, returning text. Use it to understand screenshots, charts, and documents.

Reasoning and tools

Supports reasoning and function calling. Pass tools and tool_choice; your application executes the requested tools.

Pricing

Billing follows token usage. At current prices, input is 118.8 credits per 1M tokens (about $0.594) and output is 356.4 credits per 1M tokens (about $1.782). Final charges follow actual token usage. Failed calls are not charged.

FAQ

What model id do I send?⌄

Send model glm-4-5v to POST https://modelfold.ai/v1/chat/completions with Authorization: Bearer YOUR_API_KEY and an OpenAI-style messages array. stream: true returns server-sent events.

Does it support tools?⌄

Yes. Pass tools and tool_choice as in OpenAI Chat Completions. The model returns tool arguments; your application runs the tool and sends back its result.

Rate card
Input118.8 credits 1M tokens≈ $0.59
Cached input21.78 credits 1M tokens≈ $0.11
Output356.4 credits 1M tokens≈ $1.78

Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.

Read API docs →AI Agents · Claude Code / Cursor / Trae →
Quick start
curl https://modelfold.ai/v1/chat/completions \
  -H "Authorization: Bearer $MODELFOLD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"glm-4-5v","messages":[{"role":"user","content":"Hello"}]}'