Google Gemini 3 Pro Image Text To Image API Documentation
Playground
Try it on WaveSpeedAI!Googleโs Gemini 3.0 Pro (Gemini 3.0 Pro Preview) is a cutting-edge text-to-image model enabling high-res 4K image generation optimized for phones. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
Gemini 3.0 Pro Image (Gemini 3.0 Pro Image Preview) is Googleโs lightweight yet powerful AI image generation model, built for creators who need fast, high-quality visuals from simple text prompts. It transforms words into expressive, realistic images with remarkable clarity, composition, and style diversity โ all within seconds.
๐ Why it stands out
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Instant Image Creation Generate beautiful, coherent visuals from just a short text prompt โ no design skills required.
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Versatile Visual Styles Supports realistic, illustrative, anime, and painterly outputs, adapting naturally to your creative intent.
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Accurate Text-to-Scene Understanding Accurately interprets subjects, backgrounds, and object relationships to create contextually correct compositions.
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Fast & Efficient Optimized for quick turnaround and minimal compute cost, perfect for rapid prototyping and social content.
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Clean, Balanced Lighting Produces visually appealing results without overexposure or unnatural shadows โ ideal for portraits, landscapes, and product imagery.
โ๏ธ Capabilities
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Input: text prompt
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Output: high-quality image (JPEG/PNG)
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Supports multiple aspect ratios and output format
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Compatible with descriptive prompts such as:
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โA golden retriever playing in a field of sunflowers at sunset.โ
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โA futuristic city skyline with neon reflections on wet streets.โ
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โAn elegant still-life photo of coffee and croissants by a window.โ
๐ฐ Pricing
| Resolution | Cost per image |
|---|---|
| 1k | $0.14 |
| 2k | $0.14 |
| 4k | $0.24 |
๐ก Best Use Cases
- Social Media & Marketing โ Create on-brand visuals instantly.
- Concept Art & Storyboarding โ Generate design ideas and moodboards effortlessly.
- E-commerce & Advertising โ Produce high-quality product images without photography.
- Education & Presentation โ Visualize complex ideas or creative concepts easily.
๐ Notes
Please ensure your prompts comply with Googleโs Safety Guidelines. If an error occurs, review your prompt for restricted content, adjust it, and try again.
๐ Where gemini-3-pro-image Fits In
Compare gemini-3-pro-image T2I with:
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FLUX.1 [dev] โ Nano Banana Pro Edit focuses on semantic understanding and layout-aware editing via Gemini 3โs reasoning, making it ideal for complex, text-driven transformations without manual masking. FLUX.1 [dev] emphasizes maximum resolution control and fine detail preservation for highly technical workflows.
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Stable Diffusion 3.5 โ Nano Banana Pro Edit leverages Googleโs production-scale multimodal training and advanced reasoning for context-aware edits that understand object relationships and composition. Stable Diffusion 3.5 offers open-source flexibility for custom fine-tuning and local deployment in highly specialized pipelines.
-
Gpt-Image-1 (OpenAI) โ Nano Banana Pro Edit emphasizes layout control, multilingual on-image text, and tightly directed edits for design and marketing workflows, while openai/gpt-image-1 shines as a general-purpose creative generator with strong style variety and fast, natural-language image synthesis for broad consumer and developer use.
-
Original Nano Banana (Gemini 2.5 Flash Image) โ Nano Banana Pro Edit trades pure speed for quality, delivering better reasoning, sharper text, improved character consistency, and richer camera controls at a higher unit cost. Original Nano Banana remains ideal for rapid, low-latency iterations and lightweight edits.
-
Seedream โ Nano Banana Pro Edit is tuned for reliable typography, photo-real edits, and mixed media layouts, while SeeDream excels at fast, stylized T2I generation with strong anime and illustration aesthetics, making it a good choice for heavily stylized concept art.
-
Qwen Image 2509 โ Nano Banana Pro Edit focuses on high-fidelity 4K outputs and multilingual on-image design control, whereas Qwen Image shines in open-source ecosystems and document-style rendering, offering flexible integration for developer-centric and research workflows.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic ocean wave at sunrise, highly detailed",
"aspect_ratio": "1:1",
"resolution": "1k",
"output_format": "png"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/google/gemini-3-pro-image/text-to-image" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
-H "Content-Type: application/json" \
-d "${REQUEST_BODY}")
TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body \
"${RESULT_URL}" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}")
RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')
case "${STATUS}" in
completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
esac
doneParameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| aspect_ratio | string | No | - | 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9 | The aspect ratio of the generated media. |
| resolution | string | No | 1k | 1k, 2k, 4k | The resolution of the output image. |
| output_format | string | No | png | png, jpeg | The format of the output image. |
| enable_sync_mode | boolean | No | false | - | If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models. |
| enable_base64_output | boolean | No | false | - | If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., โsuccessโ) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Output values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., โ2023-04-01T12:34:56.789Zโ) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., โsuccessโ) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<string | object> | Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to poll for the prediction result |
| data.status | string | Status: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |