# GLM Image text to image fal AI

Needs prompt.

GLM Image, served by fal.ai. $0.05 per megapixels Output is constrained to 1024x1024 and one image; reservation covers two billed megapixels, including whole-megapixel rounding. The exact receipt determines the final charge. Asynchronous: returns a request_id; poll fal/status and fetch fal/result with model "fal-ai/glm-image" and that request_id. The exact endpoint/request billing receipt is required before settlement.

- Tool ID: `fal/fal-ai-glm-image`
- Name in the catalog: GLM Image, text to image
- Provider: [fal.ai](/providers/fal.md)
- Capability: [AI image generation](/tools/image-generation.md)
- Price: $0.1 per call
- Authentication: an authorised Agentik workspace is required for execution, including zero-price tools.

## Pricing contract

The provider’s price, with no markup. Billed for measured usage.


```json
{
  "model": "per_call",
  "amountUsd": 0.1
}
```

Pricing source: [https://fal.ai/models/fal-ai/glm-image/llms.txt](https://fal.ai/models/fal-ai/glm-image/llms.txt). $0.05 per megapixels Output is constrained to 1024x1024 and one image; reservation covers two billed megapixels, including whole-megapixel rounding. The exact receipt determines the final charge..

Price verification date: 2026-11-03.

## Complete input schema


```json
{
  "type": "object",
  "properties": {
    "output_format": {
      "default": "jpeg",
      "title": "Output Format",
      "description": "Output image format.",
      "type": "string",
      "enum": [
        "jpeg",
        "png"
      ]
    },
    "num_inference_steps": {
      "default": 30,
      "maximum": 100,
      "title": "Num Inference Steps",
      "description": "Number of diffusion denoising steps. More steps generally produce higher quality images.",
      "type": "integer",
      "minimum": 10,
      "enum": [
        30
      ]
    },
    "prompt": {
      "title": "Prompt",
      "description": "Text prompt for image generation.",
      "type": "string"
    },
    "image_size": {
      "type": "object",
      "properties": {
        "width": {
          "type": "integer",
          "enum": [
            1024
          ]
        },
        "height": {
          "type": "integer",
          "enum": [
            1024
          ]
        }
      },
      "required": [
        "width",
        "height"
      ],
      "additionalProperties": false,
      "default": {
        "width": 1024,
        "height": 1024
      }
    },
    "num_images": {
      "default": 1,
      "maximum": 1,
      "title": "Num Images",
      "description": "Number of images to generate.",
      "type": "integer",
      "minimum": 1,
      "enum": [
        1
      ]
    },
    "enable_prompt_expansion": {
      "title": "Enable Prompt Expansion",
      "description": "If True, the prompt will be enhanced using an LLM for more detailed and higher quality results.",
      "type": "boolean",
      "default": false,
      "enum": [
        false
      ]
    },
    "seed": {
      "title": "Seed",
      "description": "Random seed for reproducibility. The same seed with the same prompt will produce the same image.",
      "anyOf": [
        {
          "type": "integer"
        },
        {
          "type": "null"
        }
      ]
    },
    "enable_safety_checker": {
      "title": "Enable Safety Checker",
      "description": "Enable NSFW safety checking on the generated images. Disabling it requires account authorization; unauthorized requests are always checked, and images flagged as unsafe are returned as black images.",
      "type": "boolean",
      "default": true
    },
    "guidance_scale": {
      "default": 1.5,
      "maximum": 10,
      "title": "Guidance Scale",
      "description": "Classifier-free guidance scale. Higher values make the model follow the prompt more closely.",
      "type": "number",
      "minimum": 1
    }
  },
  "required": [
    "prompt"
  ],
  "additionalProperties": false
}
```

## Published example

This is the provider tool’s published example. Replace example values with the user’s requested inputs, respecting the schema; do not execute an example merely to test a connection.


```json
{
  "tool_id": "fal/fal-ai-glm-image",
  "input": {
    "prompt": "An elegant close-up photograph of hands holding a beautifully illustrated watercolor menu card. The hands have natural sun-kissed skin with a delicate gold ring, gripping the menu gently and refined.\n\nThe menu is a work of art—hand-painted watercolor illustration on textured cream watercolor paper with soft deckled edges:\n\n- Top: \"AZURE\" painted in flowing navy blue watercolor calligraphy with organic brushstroke texture and slight color bleeding\n- Watercolor illustration border: delicate tropical elements painted in soft washes—translucent turquoise waves flowing along the edges, loose coral and pink hibiscus flowers in the corners, gentle green palm leaf strokes, and small golden paint splatters suggesting sunlight\n- Center menu items in elegant hand-lettered watercolor script with slight variations in ink density:\n\n  \"Tuna Tartare — 24\"\n  \"Sea Bass — 32\"\n  \"Mango Pavlova — 14\"\n\n- Bottom: \"Koh Samui\" in small watercolor lettering with a tiny painted wave\n\nThe watercolor has beautiful organic qualities—soft color gradients, natural paper texture visible through transparent washes, slight bleeding at edges of brushstrokes, layered translucent blues and greens creating depth. The paint has a luminous, fresh quality with white paper showing through in places.\n\nBackground: dreamy out-of-focus turquoise ocean with sparkling bokeh lights reflecting off water, creating soft circular light spots in aqua and gold tones. The blurred background complements the watercolor aesthetic perfectly.\n\nLighting: warm natural golden hour sunlight from upper left, illuminating the watercolor pigments and making them glow. The light catches the textured watercolor paper beautifully, showing subtle shadows in the paint layers and paper grain.\n\nPhotography style: shot on 85mm f/1.4, shallow depth of field with only the menu in sharp focus. High-end editorial aesthetic that celebrates the handmade, artistic quality of the watercolor. Color palette: cream paper, translucent turquoise and teal watercolors, soft coral pink, navy blue, gentle greens, golden accents, warm skin tones.\n\nThe overall mood is artistic, luxurious, handcrafted—like a boutique resort that values artistry and craftsmanship. The watercolor style feels fresh, organic, and elevated.",
    "image_size": {
      "width": 1024,
      "height": 1024
    },
    "num_images": 1,
    "enable_prompt_expansion": false,
    "num_inference_steps": 30,
    "output_format": "jpeg",
    "enable_safety_checker": true,
    "guidance_scale": 1.5
  }
}
```

## Execute and retrieve

Inspect again before execution, explain the price and obtain the required authority. Use MCP run_tool or POST /v1/run with this tool ID, valid input and an idempotency key. Save the returned run ID and follow the actual state. If Agentik answers that the tool is temporarily unavailable, do not retry it blindly; use discovery to propose an alternative.

This tool uses deferred settlement. Follow its returned task/run instructions; preserve the existing reservation until the result is reconciled.

A partial or uncertain result can still have consumed provider resources. Consult [billing](/docs/billing.md), [idempotency](/docs/idempotency.md) and [asynchronous results](/docs/async.md).

[Provider documentation](https://fal.ai/models/fal-ai/glm-image)

[REST inspection](https://api.agentik.cc/v1/tools/fal/fal-ai-glm-image) · [OpenAPI](/openapi.json) · [Connection guide](/connect.md)

---

[HTML page](/providers/fal/fal-ai-glm-image) · [Agent index](/llms.txt)