Generate a detailed 3D model from a text description with configurable texture, material, geometry, scale, and mesh options.
Related Tripo3D H3.1 Models
API Examples
Submit Example
const response = await fetch('https://api.flaq.ai/api/v1/3d/task', {
method: 'POST',
headers: {
Authorization: 'Bearer YOUR_API_KEY',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model_name: 'tripo3d-h3.1-text-to-3d',
prompt: 'A cute cartoon robot with a round head',
negative_prompt: 'blurry, deformed, extra limbs',
texture: true,
pbr: true,
texture_quality: 'standard',
geometry_quality: 'standard',
auto_size: false,
quad: false,
}),
});
const { data } = await response.json();
const taskId = data.task_id;
Polling Example
// Step 2: Poll for results
const taskId = data.task_id;
const pollResult = async (taskId) => {
const res = await fetch(`https://api.flaq.ai/api/v1/3d/${taskId}`, {
headers: { 'Authorization': 'Bearer YOUR_API_KEY' }
});
return res.json();
};
while (true) {
const pollResultData = await pollResult(taskId);
const status = pollResultData.data.task_status;
if (status === 'succeed') {
console.log(pollResultData.data.task_result.files[0].url);
break;
}
if (status === 'failed') {
console.error(pollResultData.data.task_status_msg);
break;
}
await new Promise(resolve => setTimeout(resolve, 10000));
}
Submit Example
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/3d/task',
headers={
'Authorization': 'Bearer YOUR_API_KEY',
'Content-Type': 'application/json',
},
json={
'model_name': 'tripo3d-h3.1-text-to-3d',
'prompt': 'A cute cartoon robot with a round head',
'negative_prompt': 'blurry, deformed, extra limbs',
'texture': True,
'pbr': True,
'texture_quality': 'standard',
'geometry_quality': 'standard',
'auto_size': False,
'quad': False,
},
)
response.raise_for_status()
result = response.json()
task_id = result['data']['task_id']
Polling Example
# Step 2: Poll for results
task_id = response.json()['data']['task_id']
poll_url = f"https://api.flaq.ai/api/v1/3d/{task_id}"
while True:
poll_result = requests.get(poll_url, headers={'Authorization': 'Bearer YOUR_API_KEY'}).json()
status = poll_result['data']['task_status']
if status == 'succeed':
print(poll_result['data']['task_result']['files'][0]['url'])
break
if status == 'failed':
print(poll_result['data']['task_status_msg'])
break
time.sleep(10)
Submit Example
curl -X POST "https://api.flaq.ai/api/v1/3d/task" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model_name": "tripo3d-h3.1-text-to-3d",
"prompt": "A cute cartoon robot with a round head",
"negative_prompt": "blurry, deformed, extra limbs",
"texture": true,
"pbr": true,
"texture_quality": "standard",
"geometry_quality": "standard",
"auto_size": false,
"quad": false
}'
Polling Example
# Step 2: Poll for results
# Replace {task_id} with the task_id returned from the submit response
curl -X GET "https://api.flaq.ai/api/v1/3d/{task_id}" \
-H "Authorization: Bearer YOUR_API_KEY"
Try an example
Tripo H3.1 Text to 3D Pricing
| Parameters | Price | Original Price | Discount |
|---|
README
High-Fidelity Tripo H3.1 Text-to-3D API (Professional AI 3D Asset Generation)
Tripo H3.1 Text-to-3D API by Tripo3D AI turns written ideas into detailed 3D assets for developers, studios, and product teams. Built for high-fidelity 3D generation, this Tripo H3.1 API helps you move from a natural-language description to a structured mesh with optional textures and PBR materials. Flaq AI provides a dependable API integration for taking concept prompts into game assets, product visualizations, marketing scenes, and other production workflows.
Key Features of Tripo H3.1 Text-to-3D API
- Prompt-Driven 3D Asset Creation: Describe an object’s form, style, material, and visual details in natural language, then generate a corresponding 3D model through the Tripo H3.1 API.
- High-Fidelity Geometry Generation: Create detailed meshes designed for assets that need to hold up in close-up renders, polished showcases, and demanding 3D production workflows.
- Optional Textures and PBR Materials: Generate rich surface appearance and physically based material maps when the project calls for a more complete, render-ready asset.
- Flexible Quality Direction: Balance generation requirements with configurable geometry and texture detail, helping teams match visual fidelity to the intended use of each asset.
- Scale and Topology Flexibility: Support real-world asset sizing and quad-mesh output options for workflows that need more deliberate downstream preparation.
- Production-Oriented API Integration: Bring text-to-3D generation into content pipelines, creative tools, or automated asset systems without changing the way your team builds.
How to Use Tripo H3.1 Text-to-3D API for AI Asset Creation on Flaq AI
- Input: A natural-language description of the 3D asset, including shape, material, style, and details to avoid when needed.
- Output: A generated 3D mesh with optional textures and PBR materials, returned through the Flaq AI API workflow for use in rendering, editing, and delivery pipelines.
- Quality Direction: Flexible visual-quality choices let you tailor geometry and texture richness to the needs of a concept model, hero asset, or detailed presentation.
- Asset Preparation: Choose practical sizing and topology preferences when an asset needs to fit into a more structured production workflow.
- Capabilities: Text-to-3D generation, high-detail geometry, material-aware output, and prompt-led creative control through Tripo H3.1 API integration.
Best Use Cases for Tripo H3.1 Text-to-3D API Integration
- Game and Interactive Asset Prototyping: Turn early art direction into 3D props, environment elements, and concept assets before committing to a longer modeling cycle.
- Product Concept Visualization: Create presentable 3D interpretations of product ideas for reviews, pitch decks, landing pages, and internal decision-making.
- Marketing and Brand Scenes: Build custom 3D objects for campaign visuals, animated product stories, and promotional renders from concise creative briefs.
- Creative Tool Automation: Add a text-to-3D capability to design systems, agent workflows, and content platforms that need programmatic asset generation.
- Rapid Design Exploration: Generate multiple interpretations of an idea to evaluate form, materials, and visual direction earlier in the creative process.
Note Use clear, specific prompts and ensure that every request complies with applicable content policies, intellectual-property requirements, and local laws.
Tripo H3.1 Text-to-3D vs Competitors: Comparative Analysis
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Tripo H3.1 Text-to-3D vs. Tripo H3.1 Image-to-3D: Text-to-3D is the stronger starting point when an idea exists only as a written brief. Image-to-3D is better when a reference image must anchor the asset’s appearance and silhouette.
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Tripo H3.1 Text-to-3D vs. Tripo H3.1 Multiview-to-3D: Text-to-3D offers faster concept exploration without source imagery. Multiview-to-3D is the more suitable choice when several object views are available and reference consistency is the priority.
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Tripo H3.1 Text-to-3D vs. Meshy Text-to-3D: Meshy provides a familiar AI 3D creation workflow. Tripo H3.1 Text-to-3D API emphasizes high-detail asset generation with flexible material, quality, and topology choices for Flaq AI production pipelines.
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Tripo H3.1 Text-to-3D vs. Hunyuan3D: Hunyuan3D is often explored in open-model and self-managed environments. Tripo H3.1 provides a hosted API path for teams that want detailed, material-aware asset generation without operating a 3D generation stack themselves.
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Tripo H3.1 Text-to-3D vs. Traditional 3D Modeling: Traditional modeling gives artists maximum manual control but requires substantial time and specialist effort. Tripo H3.1 accelerates the first asset pass so teams can focus their manual work on refinement and art direction.