Estimate inference price
curl --request POST \ --url https://api.app.layer.ai/api/v1/workspaces/:workspace_id/inferences/estimate \ --header 'Authorization: Bearer <token>' \ --header 'Content-Type: application/json' \ --data '{ "model_id": "<uuid>", "weight": 1, "prompt": "<string>", "width": 0, "height": 0, "batch_size": 4, "num_inference_steps": 0, "guidance_scale": 0, "prompt_strength": 0, "quality": "low", "sharpness": 0, "duration_seconds": 0, "generate_audio": true, "keep_audio": true, "fps": 0, "video_effects": [], "use_ta_pose": true, "pose_mode": "A_POSE", "include_textures": true, "quad_mesh": true, "pbr_materials": true, "low_poly": true, "generate_parts": true, "face_limit": 0, "stability": 0, "use_speaker_boost": true, "similarity_boost": 0, "style_exaggeration": 0, "speed": 0, "upscale_ratio": 0, "creativity": 0, "resemblance": 0, "vectorize": true, "remove_background": true, "reframe": true, "refill": true}'import requests
url = "https://api.app.layer.ai/api/v1/workspaces/:workspace_id/inferences/estimate"
payload = { "model_id": "<uuid>", "weight": 1, "prompt": "<string>", "width": 0, "height": 0, "batch_size": 4, "num_inference_steps": 0, "guidance_scale": 0, "prompt_strength": 0, "quality": "low", "sharpness": 0, "duration_seconds": 0, "generate_audio": True, "keep_audio": True, "fps": 0, "video_effects": [], "use_ta_pose": True, "pose_mode": "A_POSE", "include_textures": True, "quad_mesh": True, "pbr_materials": True, "low_poly": True, "generate_parts": True, "face_limit": 0, "stability": 0, "use_speaker_boost": True, "similarity_boost": 0, "style_exaggeration": 0, "speed": 0, "upscale_ratio": 0, "creativity": 0, "resemblance": 0, "vectorize": True, "remove_background": True, "reframe": True, "refill": True}headers = { "Authorization": "Bearer <token>", "Content-Type": "application/json"}
response = requests.post(url, json=payload, headers=headers)
print(response.json())const url = 'https://api.app.layer.ai/api/v1/workspaces/:workspace_id/inferences/estimate';const options = { method: 'POST', headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'}, body: '{"model_id":"<uuid>","weight":1,"prompt":"<string>","width":0,"height":0,"batch_size":4,"num_inference_steps":0,"guidance_scale":0,"prompt_strength":0,"quality":"low","sharpness":0,"duration_seconds":0,"generate_audio":true,"keep_audio":true,"fps":0,"video_effects":[],"use_ta_pose":true,"pose_mode":"A_POSE","include_textures":true,"quad_mesh":true,"pbr_materials":true,"low_poly":true,"generate_parts":true,"face_limit":0,"stability":0,"use_speaker_boost":true,"similarity_boost":0,"style_exaggeration":0,"speed":0,"upscale_ratio":0,"creativity":0,"resemblance":0,"vectorize":true,"remove_background":true,"reframe":true,"refill":true}'};
try { const response = await fetch(url, options); const data = await response.json(); console.log(data);} catch (error) { console.error(error);}package main
import ( "fmt" "strings" "net/http" "io")
func main() {
url := "https://api.app.layer.ai/api/v1/workspaces/:workspace_id/inferences/estimate"
payload := strings.NewReader("{\n \"model_id\": \"<uuid>\",\n \"weight\": 1,\n \"prompt\": \"<string>\",\n \"width\": 0,\n \"height\": 0,\n \"batch_size\": 4,\n \"num_inference_steps\": 0,\n \"guidance_scale\": 0,\n \"prompt_strength\": 0,\n \"quality\": \"low\",\n \"sharpness\": 0,\n \"duration_seconds\": 0,\n \"generate_audio\": true,\n \"keep_audio\": true,\n \"fps\": 0,\n \"video_effects\": [],\n \"use_ta_pose\": true,\n \"pose_mode\": \"A_POSE\",\n \"include_textures\": true,\n \"quad_mesh\": true,\n \"pbr_materials\": true,\n \"low_poly\": true,\n \"generate_parts\": true,\n \"face_limit\": 0,\n \"stability\": 0,\n \"use_speaker_boost\": true,\n \"similarity_boost\": 0,\n \"style_exaggeration\": 0,\n \"speed\": 0,\n \"upscale_ratio\": 0,\n \"creativity\": 0,\n \"resemblance\": 0,\n \"vectorize\": true,\n \"remove_background\": true,\n \"reframe\": true,\n \"refill\": true\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>") req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close() body, _ := io.ReadAll(res.Body)
fmt.Println(res) fmt.Println(string(body))
}<?php
$curl = curl_init();
curl_setopt_array($curl, [ CURLOPT_URL => "https://api.app.layer.ai/api/v1/workspaces/:workspace_id/inferences/estimate", CURLOPT_RETURNTRANSFER => true, CURLOPT_ENCODING => "", CURLOPT_MAXREDIRS => 10, CURLOPT_TIMEOUT => 30, CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1, CURLOPT_CUSTOMREQUEST => "POST", CURLOPT_POSTFIELDS => json_encode([ 'model_id' => '<uuid>', 'weight' => 1, 'prompt' => '<string>', 'width' => 0, 'height' => 0, 'batch_size' => 4, 'num_inference_steps' => 0, 'guidance_scale' => 0, 'prompt_strength' => 0, 'quality' => 'low', 'sharpness' => 0, 'duration_seconds' => 0, 'generate_audio' => null, 'keep_audio' => null, 'fps' => 0, 'video_effects' => [
], 'use_ta_pose' => null, 'pose_mode' => 'A_POSE', 'include_textures' => null, 'quad_mesh' => null, 'pbr_materials' => null, 'low_poly' => null, 'generate_parts' => null, 'face_limit' => 0, 'stability' => 0, 'use_speaker_boost' => null, 'similarity_boost' => 0, 'style_exaggeration' => 0, 'speed' => 0, 'upscale_ratio' => 0, 'creativity' => 0, 'resemblance' => 0, 'vectorize' => null, 'remove_background' => null, 'reframe' => null, 'refill' => null ]), CURLOPT_HTTPHEADER => [ "Authorization: Bearer <token>", "Content-Type: application/json" ],]);
$response = curl_exec($curl);$err = curl_error($curl);
curl_close($curl);
if ($err) { echo "cURL Error #:" . $err;} else { echo $response;}OkHttpClient client = new OkHttpClient();
MediaType mediaType = MediaType.parse("application/json");RequestBody body = RequestBody.create(mediaType, "{\n \"model_id\": \"<uuid>\",\n \"weight\": 1,\n \"prompt\": \"<string>\",\n \"width\": 0,\n \"height\": 0,\n \"batch_size\": 4,\n \"num_inference_steps\": 0,\n \"guidance_scale\": 0,\n \"prompt_strength\": 0,\n \"quality\": \"low\",\n \"sharpness\": 0,\n \"duration_seconds\": 0,\n \"generate_audio\": true,\n \"keep_audio\": true,\n \"fps\": 0,\n \"video_effects\": [],\n \"use_ta_pose\": true,\n \"pose_mode\": \"A_POSE\",\n \"include_textures\": true,\n \"quad_mesh\": true,\n \"pbr_materials\": true,\n \"low_poly\": true,\n \"generate_parts\": true,\n \"face_limit\": 0,\n \"stability\": 0,\n \"use_speaker_boost\": true,\n \"similarity_boost\": 0,\n \"style_exaggeration\": 0,\n \"speed\": 0,\n \"upscale_ratio\": 0,\n \"creativity\": 0,\n \"resemblance\": 0,\n \"vectorize\": true,\n \"remove_background\": true,\n \"reframe\": true,\n \"refill\": true\n}");Request request = new Request.Builder() .url("https://api.app.layer.ai/api/v1/workspaces/:workspace_id/inferences/estimate") .post(body) .addHeader("Authorization", "Bearer <token>") .addHeader("Content-Type", "application/json") .build();
Response response = client.newCall(request).execute();require 'uri'require 'net/http'
url = URI("https://api.app.layer.ai/api/v1/workspaces/:workspace_id/inferences/estimate")
http = Net::HTTP.new(url.host, url.port)http.use_ssl = true
request = Net::HTTP::Post.new(url)request["Authorization"] = 'Bearer <token>'request["Content-Type"] = 'application/json'request.body = "{\n \"model_id\": \"<uuid>\",\n \"weight\": 1,\n \"prompt\": \"<string>\",\n \"width\": 0,\n \"height\": 0,\n \"batch_size\": 4,\n \"num_inference_steps\": 0,\n \"guidance_scale\": 0,\n \"prompt_strength\": 0,\n \"quality\": \"low\",\n \"sharpness\": 0,\n \"duration_seconds\": 0,\n \"generate_audio\": true,\n \"keep_audio\": true,\n \"fps\": 0,\n \"video_effects\": [],\n \"use_ta_pose\": true,\n \"pose_mode\": \"A_POSE\",\n \"include_textures\": true,\n \"quad_mesh\": true,\n \"pbr_materials\": true,\n \"low_poly\": true,\n \"generate_parts\": true,\n \"face_limit\": 0,\n \"stability\": 0,\n \"use_speaker_boost\": true,\n \"similarity_boost\": 0,\n \"style_exaggeration\": 0,\n \"speed\": 0,\n \"upscale_ratio\": 0,\n \"creativity\": 0,\n \"resemblance\": 0,\n \"vectorize\": true,\n \"remove_background\": true,\n \"reframe\": true,\n \"refill\": true\n}"
response = http.request(request)puts response.read_bodyvar client = new RestClient("https://api.app.layer.ai/api/v1/workspaces/:workspace_id/inferences/estimate");var request = new RestRequest("", Method.Post);request.AddHeader("Authorization", "Bearer <token>");request.AddHeader("Content-Type", "application/json");request.AddParameter("application/json", "{\n \"model_id\": \"<uuid>\",\n \"weight\": 1,\n \"prompt\": \"<string>\",\n \"width\": 0,\n \"height\": 0,\n \"batch_size\": 4,\n \"num_inference_steps\": 0,\n \"guidance_scale\": 0,\n \"prompt_strength\": 0,\n \"quality\": \"low\",\n \"sharpness\": 0,\n \"duration_seconds\": 0,\n \"generate_audio\": true,\n \"keep_audio\": true,\n \"fps\": 0,\n \"video_effects\": [],\n \"use_ta_pose\": true,\n \"pose_mode\": \"A_POSE\",\n \"include_textures\": true,\n \"quad_mesh\": true,\n \"pbr_materials\": true,\n \"low_poly\": true,\n \"generate_parts\": true,\n \"face_limit\": 0,\n \"stability\": 0,\n \"use_speaker_boost\": true,\n \"similarity_boost\": 0,\n \"style_exaggeration\": 0,\n \"speed\": 0,\n \"upscale_ratio\": 0,\n \"creativity\": 0,\n \"resemblance\": 0,\n \"vectorize\": true,\n \"remove_background\": true,\n \"reframe\": true,\n \"refill\": true\n}", ParameterType.RequestBody);var response = client.Execute(request);Estimate the Creative Units cost of an inference with given parameters.
Authorizations
Section titled “Authorizations”Parameters
Section titled “Parameters”Path Parameters
Section titled “Path Parameters”Request Bodyrequired
Section titled “Request Bodyrequired”REST request body for estimating inference price. workspace_id comes from path.
object
Model/style ID to use for generation.
Style/LoRA strength applied to the model. 1.0 = as trained; lower weakens, higher over-applies the style. Only affects LoRA/adapter-backed styles; ignored for models without a trainable adapter.
Number of outputs (1-16).
Canonical rest pose a character-mesh model is asked to generate in.
A_POSE places the arms angled down at roughly 45°; T_POSE holds them
straight out to the sides. Only meaningful for models that advertise the
pose_modes capability (e.g. Meshy V7).
Deliberately a light top-level module (like base_model_id), NOT under
pkg.models.inference: the Blueprint definition layer registers this as a
BlueprintType and migrates legacy node ports, and must do so without pulling
in the heavy pkg.models.inference package, which would perturb the Temporal
workflow-sandbox import graph and split pydantic class identity.
Responses
Section titled “Responses”Successful Response
object
Total estimated Creative Units price for this run.
Usable Creative Units balance (total balance minus reserved by in-progress generations).
Usable balance after subtracting the estimated price. Can be negative.
Whether the workspace has enough available Creative Units to cover the estimated price.
Examplegenerated
{ "estimated_price_creative_units": 1, "workspace_balance_creative_units": 1, "estimated_remaining_balance_creative_units": 1, "has_sufficient_creative_units": true}Unauthenticated — missing or invalid Bearer token.
object
Example
{ "type": "https://api.layer.ai/errors/ERROR_CODE", "title": "Error Title", "status": 400, "detail": "Human-readable description."}Forbidden — insufficient permissions.
object
Example
{ "type": "https://api.layer.ai/errors/ERROR_CODE", "title": "Error Title", "status": 400, "detail": "Human-readable description."}Resource not found.
object
Example
{ "type": "https://api.layer.ai/errors/ERROR_CODE", "title": "Error Title", "status": 400, "detail": "Human-readable description."}Invalid input parameters.
object
Example
{ "type": "https://api.layer.ai/errors/ERROR_CODE", "title": "Error Title", "status": 400, "detail": "Human-readable description."}Rate limited — too many concurrent requests.
object
Example
{ "type": "https://api.layer.ai/errors/ERROR_CODE", "title": "Error Title", "status": 400, "detail": "Human-readable description."}Internal server error.
object
Example
{ "type": "https://api.layer.ai/errors/ERROR_CODE", "title": "Error Title", "status": 400, "detail": "Human-readable description."}