Hi3D V3.0 Image-to-3D converts a single reference image into a detailed 3D mesh with optional textures, PBR materials, and multiple export formats for game assets, product visualization, 3D design, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Idle
$2.3per run

Hi3D V3.0 Image to 3D converts one reference image into a detailed 3D mesh. It supports texture generation, PBR material maps, configurable face count, and multiple 3D export formats including GLB, OBJ, STL, FBX, and USDZ.
Single-image 3D generation
Create a detailed 3D model from one reference image.
Quality and master modes
Choose 2048quality for faster generation or 2048master for higher-quality output.
Texture and PBR support
Generate textured 3D assets and optional PBR material maps for more production-ready results.
Configurable geometry
Set a target face count for different quality, detail, or downstream workflow needs.
Multiple export formats
Export generated models as glb, obj, stl, fbx, or usdz.
Shading control
Adjust de-shading strength to improve texture and material consistency.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Input PNG, JPEG, or WebP image. Maximum file size: 20 MB. |
| resolution | No | Generation quality mode: 2048quality for faster generation or 2048master for the highest quality. |
| enable_texture | No | Generate textures in addition to geometry. Default: true. |
| enable_pbr | No | Generate PBR material maps with the texture. Default: true. Ignored when enable_texture is disabled. |
| face_count | No | Target face count for the generated mesh. Range: 100000–5000000. |
| export_format | No | Output format: glb, obj, stl, fbx, or usdz. |
| shading | No | De-shading strength. Range: 0–1. Default: 0.5. |
2048quality for faster generation or 2048master for higher-quality output.enable_texture enabled when you need textured output.enable_pbr enabled when PBR material maps are needed.glb, obj, stl, fbx, or usdz.shading to control de-shading strength.Pricing is based on selected resolution, texture generation, and PBR generation.
| Resolution | Geometry only | Texture | Texture + PBR |
|---|---|---|---|
| 2048quality | $1.98 | $2.20 | $2.31 |
| 2048master | $9.68 | $9.90 | $10.01 |
PBR is only generated and priced when texture generation is enabled.
2048quality for faster iteration and 2048master for higher-quality final assets.face_count based on the target workflow: lower for real-time use, higher for detail preservation.glb for general-purpose 3D workflows and usdz when USDZ output is required.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/hitem3d/hi3d-v3.0/image-to-3d with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Hi3d v3.0 Image To 3d below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"resolution": "2048quality",
"enable_texture": true,
"enable_pbr": true,
"face_count": 2000000,
"export_format": "glb",
"shading": 0.5
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/hitem3d/hi3d-v3.0/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=$(printf '%s' "$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' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/hitem3d/hi3d-v3.0/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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
"resolution": "2048quality",
"enable_texture": true,
"enable_pbr": true,
"face_count": 2000000,
"export_format": "glb",
"shading": 0.5
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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"].includes(result.status)) throw new Error(JSON.stringify(result));
if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
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",
"resolution": "2048quality",
"enable_texture": True,
"enable_pbr": True,
"face_count": 2000000,
"export_format": "glb",
"shading": 0.5
}
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/hitem3d/hi3d-v3.0/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 = task.get("urls", {}).get("get") or 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"}:
raise RuntimeError(result)
if status not in {"created", "processing"}:
raise RuntimeError(f"Unexpected status: {status}")
time.sleep(2)Hi3d v3.0 Image To 3d is a Hitem3d model for 3D asset generation from images, exposed as a REST API on WaveSpeedAI. Hi3D V3.0 Image-to-3D converts a single reference image into a detailed 3D mesh with optional textures, PBR materials, and multiple export formats for game assets, product visualization, 3D design, and production workflows. 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 production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/hitem3d/hitem3d-hi3d-v3.0-image-to-3d.
Hi3d v3.0 Image To 3d starts at $2.30 per run. 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`, `resolution`, `enable_pbr`, `enable_texture`, `export_format`, `face_count`. 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/hitem3d/hitem3d-hi3d-v3.0-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 (Hitem3d). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.