how much does Meshy 7.1 cost?

$0.0127/Meshy credit (20 base + 10-15 texture + 5 hi-res geo). you pay per run from your inference shell credits. no subscription is required.

how do I run Meshy 7.1 via api?

call meshy/meshy-7-1 with the javascript or python sdk, the rest api, or `belt app run meshy/meshy-7-1` from a terminal. the api reference on this page lists every input.

Meshy 7.1 is made by meshy and runs on inference shell. every meshy app is listed at https://inference.sh/apps/meshy.

can my agent use Meshy 7.1?

yes. agents call it as a tool through the inference shell mcp server (https://api.inference.sh/mcp), the belt cli or the sdk, and pay per run like you do.

what are the alternatives to Meshy 7.1?

other 3d apps on inference shell include Tripo Auto Rig, Hunyuan 3D Auto Rigging, Hunyuan 3D 3.1, Rodin Gen-2.5. they run through the same api, so switching is a one-line change.

Meshy 7.1

Meshy 7.1 3D model generation from a text prompt, one image, or up to four views. Textured or bare mesh, PBR maps, quad or triangle topology, GLB, FBX, OBJ, STL, USDZ or 3MF.

text to 3d image to 3d

run in browser →run via API run with your agent

maker: meshy
category: 3d
input → output: text → 3d, image → 3d
runs via: api, javascript and python sdk, belt cli, mcp
updated: 2026-10-28
price: $0.0127/Meshy credit (20 base + 10-15 texture + 5 hi-res geo)

api reference

about

meshy 7.1 3d model generation from a text prompt, one image, or up to four views. textured or bare mesh, pbr maps, quad or triangle topology, glb, fbx, obj, stl, usdz or 3mf.

get an api key

create one in settings → api keys. the examples read it from INFERENCE_API_KEY.

bash

1export INFERENCE_API_KEY="inf_your_key"

1. calling the api

install the client

nothing to install. any http client works; the examples use curl, and jq to read responses. every response wraps its result in a data field.

run and get result

send "wait": true to hold the connection until the task finishes. without it the call returns right away with the task still running.

bash

12# "wait": true holds the connection until the task finishes.3# the response is {"data": {"id", "status", "status_text", "output", ...}}4curl -X POST https://api.inference.sh/apps/run \5  -H "Authorization: Bearer $INFERENCE_API_KEY" \6  -H "Content-Type: application/json" \7  -d '{8    "app": "meshy/meshy-7-1",9    "input": {10      "prompt": "a weathered bronze statue of a fox sitting upright"11    },12    "wait": true13  }'

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks. send "stream": true and the response is a server-sent event stream that ends when the task does.

bash

12# "stream": true answers with server-sent events until the task finishes3curl -N -X POST https://api.inference.sh/apps/run \4  -H "Authorization: Bearer $INFERENCE_API_KEY" \5  -H "Content-Type: application/json" \6  -d '{7    "app": "meshy/meshy-7-1",8    "input": {9      "prompt": "a weathered bronze statue of a fox sitting upright"10    },11    "stream": true12  }'

run in the background

start the task and get its id back right away, then check on it later. for long tasks, or when you'd rather be called back, see webhooks.

bash

1# without "wait" the call returns the task right away (status 1, "received")2TASK_ID=$(curl -s -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "meshy/meshy-7-1",7    "input": {8      "prompt": "a weathered bronze statue of a fox sitting upright"9    }10  }' | jq -r '.data.id')1112# later: read its state. done when status is 10 (completed), 11 (failed) or 12 (cancelled)13curl -s https://api.inference.sh/tasks/$TASK_ID \14  -H "Authorization: Bearer $INFERENCE_API_KEY" | jq '.data | {status, status_text, output}'

2. authentication

the api uses api keys for authentication. see the authentication docs for detailed setup instructions.

3. files

file inputs are automatically handled by the sdk. you can pass local paths, urls, or base64 data.

automatic upload

pass urls directly or use data uris for inline content.

bash

1# pass URLs or data URIs as input values2curl -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "meshy/meshy-7-1",7    "input": {8      "image": "https://example.com/image.png",9      "audio": "data:audio/mp3;base64,..."10    },11    "wait": true12  }'

manual upload

you can also upload files manually and use the returned url.

bash

1# 1. create the file: the response has an upload_url and the file's uri2FILE=$(curl -s -X POST https://api.inference.sh/files \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{"files": [{"filename": "image.png", "content_type": "image/png"}]}')67# 2. PUT the bytes to upload_url8curl -X PUT "$(echo "$FILE" | jq -r '.data[0].upload_url')" \9  -H "Content-Type: image/png" \10  --data-binary @image.png1112# 3. pass the uri as an input value13echo "$FILE" | jq -r '.data[0].uri'

4. webhooks

get notified when a task completes by providing a webhook url. when the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your url with the task result.

bash

1curl -X POST https://api.inference.sh/apps/run \2  -H "Authorization: Bearer $INFERENCE_API_KEY" \3  -H "Content-Type: application/json" \4  -d '{5    "app": "meshy/meshy-7-1",6    "input": {7        "prompt": "a weathered bronze statue of a fox sitting upright"8    },9    "webhook": "https://your-server.com/webhook"10  }'

webhook payload

your endpoint receives a JSON POST with the task result:

json

1{2  "event": "task.completed",3  "timestamp": "2024-01-15T10:30:05Z",4  "data": {5    "id": "task_abc123",6    "short_id": "abc123",7    "status": 10,8    "status_text": "completed",9    "output": { ... },10    "created_at": "2024-01-15T10:30:00Z",11    "updated_at": "2024-01-15T10:30:05Z"12  }13}

eventstringtask.completed, task.failed or task.cancelled

timestampstringiso timestamp of the delivery

data.idstringtask id

data.short_idstringshort task id

data.statusnumberterminal status (10=completed, 11=failed, 12=cancelled, 13=rejected)

data.status_textstringthe status as a word: completed, failed or cancelled

data.outputobjecttask output (when completed)

data.errorstringerror message (when failed, omitted otherwise)

data.session_idstringsession id (when the task ran in a session, omitted otherwise)

data.created_atstringiso timestamp

data.updated_atstringiso timestamp

5. schema

input

promptstring

what to make, for text to 3d. used when no images are given.

example: "a weathered bronze statue of a fox sitting upright"maxLength:800

imagesarray

one image of the object, or two to four views of it with the front view first. jpg, png or webp.

should_textureboolean

texture the mesh. off returns the bare mesh and costs less.

default: true

enable_pbrboolean

add metallic, roughness and normal maps. needs should_texture.

default: false

texture_resolutionstring

texture size. 8k costs more.

default: "2k"

options:"2k""4k""8k"

texture_promptstring

text that guides the texture. takes precedence over texture_image.

maxLength:800

texture_imagestring(file)

an image whose look the texture should follow.

geometry_resolutionstring

mesh detail. 2k and 4k cost 5 credits more; 4k is not available with several images.

default: "standard"

options:"standard""2k""4k"

topologystring

polygon type of the mesh.

default: "triangle"

options:"triangle""quad"

should_remeshboolean

remesh to target_polycount and topology.

default: false

target_polycountinteger

polygon count when remeshing, 100 to 300000. empty: 30000.

min:100max:300000

pose_modestring

put a character in an a or t pose. empty: as given.

default: ""

options:"""a-pose""t-pose"

image_enhancementboolean

let meshy clean up the input images first.

default: true

auto_sizeboolean

scale the model to a real-world size.

default: false

origin_atstring

where the origin sits with auto_size.

default: "bottom"

options:"bottom""center"

formatstring

file format of the model.

default: "glb"

options:"glb""fbx""obj""stl""usdz""3mf"

moderationboolean

have meshy refuse harmful prompts and images.

default: false

output

modelstring(file)*

the 3d model.

texturesarray

texture maps: base color, and metallic, roughness and normal with pbr.

thumbnailstring(file)

a preview render of the model.

other 3d apps

Tripo Auto Rig

tripo/tripo-rig

$0.01/credit (rig check free, auto rig 25 credits, retarget 10 credits/animation)

Hunyuan 3D Auto Rigging

tencent/hunyuan-3d-auto-rigging

$0.02/credit, 10 credits/call ($0.20/call)

Hunyuan 3D 3.1

tencent/hunyuan-3d-3-1

$0.02/credit; Geometry 15cr, Normal 25cr, +10cr views/PBR/face-count

Rodin Gen-2.5

hyper3d/rodin-gen-2-5

$0.58/credit; Extreme-High tier +0.5 credits, texture extreme-high +2 credits

Tripo 3.1

tripo/tripo-3-1

$0.01/credit, $0.10-$0.50/run (text: 10-40 credits, image/multiview: 20-50 credits)

new models

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from the blog

Meshy 7.1

api reference

about

get an api key

1. calling the api

install the client

run and get result

stream live updates

run in the background

2. authentication

3. files

automatic upload

manual upload

4. webhooks

5. schema

input

output

other 3d apps

new models

ready to run Meshy 7.1?