# Tripo v2.5 Image-to-3D > Turn a single object or product photo into a downloadable, textured 3D mesh (GLB) ready for games, AR, and product viewers. ## Overview - **Endpoint**: `https://queue.modelrunner.run/tripo3d/tripo/v2.5/image-to-3d` - **Model ID**: `tripo3d/tripo/v2.5/image-to-3d` - **Category**: image-to-3d - **Kind**: inference - **Tags**: tripo, tripo3d, image-to-3d, 3d, 3d-generation, mesh, glb ## Pricing - **Price**: $0.3 per output ## Request Lifecycle This model runs on the ModelRunner **asynchronous queue API** — a single POST does not return the output. Every call requires an `Authorization: Key $MODEL_RUNNER_KEY` header. Run three steps: 1. **Submit** — `POST https://queue.modelrunner.run/tripo3d/tripo/v2.5/image-to-3d` with a JSON body holding the input fields at the top level. The body may also include a reserved top-level `metadata` object — a flat string map (max 16 keys, key ≤64 / value ≤512 chars) stored on the request for your own tagging. It is never sent to the model; filter your request history with `GET https://queue.modelrunner.run/requests?metadata=` (exact key=value matches, AND-ed). The response carries request handles only (no output yet): ```json { "status": "IN_QUEUE", "request_id": "<21-char id>", "status_url": "https://queue.modelrunner.run/tripo3d/tripo/v2.5/image-to-3d/requests//status", "response_url": "https://queue.modelrunner.run/tripo3d/tripo/v2.5/image-to-3d/requests/", "cancel_url": "https://queue.modelrunner.run/tripo3d/tripo/v2.5/image-to-3d/requests//cancel" } ``` 2. **Poll status** — `GET ` until `status` is `COMPLETED`. Possible values are `IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`, `CANCELLED`. A `FAILED` request responds with HTTP 400 and an `error` field. 3. **Read result** — `GET `. Returns the finished request, including the generated `output`: ```json { "id": "", "status": "COMPLETED", "output": ..., "input": ... } ``` The JavaScript and Python SDKs below perform steps 2–3 for you. In any language without an SDK (Swift, Go, Kotlin, etc.) you must implement the polling loop and the final result fetch yourself — see the cURL example for the full flow. ### Input Schema - **`seed`** (`integer`, _optional_): Random seed controlling geometry generation. Reuse the same seed to reproduce the same shape. - **`auto_size`** (`boolean`, _optional_): Automatically scale the model to real-world dimensions in meters. - Default: `false` - **`image_url`** (`string`, _required_): The photo of the object, product, character, or prop to reconstruct into a 3D model. - **`face_limit`** (`integer`, _optional_): Caps the number of faces (triangles) on the output mesh. Leave unset to let mesh density adapt to the object. - **`orientation`** (`OrientationEnum`, _optional_): Set to align_image to rotate the model so it matches the input image's pose; default keeps the canonical orientation. - Default: `"default"` - Options: `"default"`, `"align_image"` - **`texture_seed`** (`integer`, _optional_): Random seed controlling texture generation. Reuse with the same seed to keep the shape but vary or reproduce textures. - **`texture_alignment`** (`TextureAlignmentEnum`, _optional_): Whether to prioritize aligning textures to the original image or to the generated geometry. - Default: `"original_image"` - Options: `"original_image"`, `"geometry"` ### Output Schema _No `Output` schema properties are available._ ## Default Example **Input** ```json { "auto_size": false, "image_url": "https://media.modelrunner.ai/vAtzF0EatRy34GsA-photo-1503602642458-232111445657", "orientation": "default", "texture_alignment": "original_image" } ``` **Output** ```json "https://media.modelrunner.ai/cLCcB6MWYZeOwjlgOJdzI.octet-stream" ``` ## Usage Examples ### cURL The queue API is asynchronous: submit the request, poll `status_url` until it is `COMPLETED`, then read the result from `response_url`. Requires `jq`. ```bash # 1. Submit the request (returns request handles, not the output) SUBMIT=$(curl --silent --request POST \ --url https://queue.modelrunner.run/tripo3d/tripo/v2.5/image-to-3d \ --header "Authorization: Key $MODEL_RUNNER_KEY" \ --header "Content-Type: application/json" \ --data '{ "auto_size": false, "image_url": "https://media.modelrunner.ai/vAtzF0EatRy34GsA-photo-1503602642458-232111445657", "orientation": "default", "texture_alignment": "original_image" }') STATUS_URL=$(echo "$SUBMIT" | jq -r '.status_url') RESPONSE_URL=$(echo "$SUBMIT" | jq -r '.response_url') # 2. Poll until the request leaves the queue / in-progress state while true; do STATUS=$(curl --silent --url "$STATUS_URL" \ --header "Authorization: Key $MODEL_RUNNER_KEY" | jq -r '.status') echo "Status: $STATUS" case "$STATUS" in COMPLETED) break ;; FAILED|CANCELLED) echo "Request $STATUS"; exit 1 ;; esac sleep 1 done # 3. Read the finished request, including the generated output curl --silent --url "$RESPONSE_URL" \ --header "Authorization: Key $MODEL_RUNNER_KEY" ``` ### JavaScript ```javascript import { modelrunner } from "@modelrunner/client"; const result = await modelrunner.subscribe("tripo3d/tripo/v2.5/image-to-3d", { input: { "auto_size": false, "image_url": "https://media.modelrunner.ai/vAtzF0EatRy34GsA-photo-1503602642458-232111445657", "orientation": "default", "texture_alignment": "original_image" } }); console.log(result.data); ``` ### Python ```python import asyncio import modelrunner_ai async def main(): response = await modelrunner_ai.submit_async( "tripo3d/tripo/v2.5/image-to-3d", arguments={ "auto_size": false, "image_url": "https://media.modelrunner.ai/vAtzF0EatRy34GsA-photo-1503602642458-232111445657", "orientation": "default", "texture_alignment": "original_image" } ) result = await response.get() print(result["output"]) asyncio.run(main()) ``` ## Additional Resources - [Playground](https://modelrunner.ai/models/tripo3d/tripo/v2.5/image-to-3d) - [OpenAPI Schema](https://modelrunner.ai/models/tripo3d/tripo/v2.5/image-to-3d/openapi.json) - [LLM Instructions](https://modelrunner.ai/models/tripo3d/tripo/v2.5/image-to-3d/llms.txt)