Meshy 7.1 Image-to-3D turns a single image into a textured 3D model. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$1.44per run
Meshy 7.1 Image-to-3D generates a 3D model from a single image. Choose geometry-only or textured output, adjust mesh settings, and optionally add rigging or an animation to a humanoid character.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Image of the object to generate (JPEG, PNG or WebP). |
| model_type | No | Choose standard or smart-topology. Smart Topology creates a lower-poly, triangle-only mesh. Default: standard. |
| geometry_resolution | No | Geometry detail: standard, 2k or 4k. Default: standard. Use standard with Smart Topology. |
| should_texture | No | Generate textures for the model. Default: true. Turn off for geometry only. |
| texture_prompt | No | Optional text description to guide the texture. |
| texture_image | No | Optional image to guide the texture. If both texture references are supplied, texture_prompt takes priority. |
| enable_pbr | No | Request metallic, roughness and normal maps when generating textures. Default: false. |
| texture_resolution | No | Texture size: 2k, 4k or 8k. Applies when textures are generated. Default: 2k. |
| topology | No | Remeshed face type: triangle or quad. Default: triangle. Smart Topology uses triangles. |
| target_polycount | No | Target face count for remeshing: 100–300000. Default: 30000. Smart Topology uses 100–30000. |
| should_remesh | No | Remesh toward the selected face count and topology. Default: true. Does not apply to Smart Topology. |
| symmetry_mode | No | Compatibility setting with no effect on the result. Options: off, auto, on. Default: auto. |
| pose_mode | No | Optional character pose: a-pose or t-pose. |
| remove_lighting | No | Optional lighting-removal setting. See Notes for availability. |
| auto_size | No | Estimate the object’s real-world size and scale it accordingly. Default: false. |
| image_enhancement | No | Optional input-image enhancement. Leave unset in Smart Topology mode. |
| enable_rigging | No | Add a skeleton to a textured humanoid character. Default: false. |
| rigging_height_meters | No | Approximate character height in meters for rigging. Default: 1.7. |
| enable_animation | No | Rig the character and apply one action selected by animation_action_id. Default: false. |
| animation_action_id | No | Animation action ID to apply when animation is enabled. Default: 92. |
| Generation option | Price per request |
|---|---|
| Standard · Geometry only | $0.96 |
| Standard · With 2k or 4k textures | $1.44 |
| Standard · With 8k textures | $1.68 |
| Smart Topology · Geometry only | $0.24 |
| Smart Topology · With 2k or 4k textures | $0.72 |
| Smart Topology · With 8k textures | $0.96 |
| Optional addition | Extra charge |
|---|---|
| Ultra geometry in standard mode | $0.24 |
| Rigging | $0.24 |
| One animation action, excluding rigging | $0.144 |
Enabling animation also includes rigging, for a total extra charge of $0.384. Enabling both rigging and animation does not charge for rigging twice.
The total is the generation price plus the selected additions. Texture resolution does not add a charge when generating geometry only.
should_texture=false, texture options are not applied.texture_prompt or texture_image to guide texturing. If both are provided, the text prompt takes priority.target_polycount.should_remesh does not affect this mode.geometry_resolution=standard with Smart Topology.remove_lighting unset for this model.image_enhancement and remove_lighting unset in Smart Topology mode.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/meshy/v7.1/image-to-3d with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for v7.1 Image To 3d below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"model_type": "standard",
"geometry_resolution": "standard",
"should_texture": true,
"enable_pbr": false,
"texture_resolution": "2k",
"topology": "triangle",
"target_polycount": 30000,
"should_remesh": true,
"symmetry_mode": "auto",
"pose_mode": "a-pose",
"auto_size": false,
"enable_rigging": false,
"rigging_height_meters": 1.7,
"enable_animation": false,
"animation_action_id": 92
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/meshy/v7.1/image-to-3d" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/meshy/v7.1/image-to-3d";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"model_type": "standard",
"geometry_resolution": "standard",
"should_texture": true,
"enable_pbr": false,
"texture_resolution": "2k",
"topology": "triangle",
"target_polycount": 30000,
"should_remesh": true,
"symmetry_mode": "auto",
"pose_mode": "a-pose",
"auto_size": false,
"enable_rigging": false,
"rigging_height_meters": 1.7,
"enable_animation": false,
"animation_action_id": 92
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"model_type": "standard",
"geometry_resolution": "standard",
"should_texture": True,
"enable_pbr": False,
"texture_resolution": "2k",
"topology": "triangle",
"target_polycount": 30000,
"should_remesh": True,
"symmetry_mode": "auto",
"pose_mode": "a-pose",
"auto_size": False,
"enable_rigging": False,
"rigging_height_meters": 1.7,
"enable_animation": False,
"animation_action_id": 92
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/meshy/v7.1/image-to-3d", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout", "deleted"}:
raise RuntimeError(result)
time.sleep(2)v7.1 Image To 3d is a Meshy model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Meshy 7.1 Image-to-3D turns a single image into a textured 3D model. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/meshy/meshy-v7.1-image-to-3d.
v7.1 Image To 3d starts at $1.44 per run or per second. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `image`, `animation_action_id`, `auto_size`, `enable_animation`, `enable_pbr`, `enable_rigging`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/meshy/meshy-v7.1-image-to-3d.
Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.
Commercial usage rights depend on the model's license, set by its provider (Meshy). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.