how much does Grok Imagine Image 2.0 cost?

$0.04/img low 1k, $0.06/img low 2k, $0.06/img med 1k, $0.08/img med 2k; $0.01/source img (edits). you pay per run from your inference shell credits. no subscription is required.

how do I run Grok Imagine Image 2.0 via api?

call xai/grok-imagine-image-2-0 with the javascript or python sdk, the rest api, or `belt app run xai/grok-imagine-image-2-0` from a terminal. the api reference on this page lists every input.

who makes Grok Imagine Image 2.0?

Grok Imagine Image 2.0 is made by xai and runs on inference shell. every xai app is listed at https://inference.sh/apps/xai.

can my agent use Grok Imagine Image 2.0?

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 Grok Imagine Image 2.0?

other image apps on inference shell include GPT Image 2.6 Flare, GPT Image 2.6 Sunburst, Gemini Nano Banana 2.1, GPT Image 2.5 Sunburst. they run through the same api, so switching is a one-line change.

Grok Imagine Image 2.0

Generate and edit images with xAI's Grok Imagine Image 2.0. Text-to-image or editing with up to 5 source images, low or medium quality, 1K or 2K output.

text to image image to image image editing

run in browser →run via API run with your agent

maker: xai
category: image
input → output: text → image, image → image
runs via: api, javascript and python sdk, belt cli, mcp
updated: 2026-11-06
price: $0.04/img low 1k, $0.06/img low 2k, $0.06/img med 1k, $0.08/img med 2k; $0.01/source img (edits)

api reference

about

generate and edit images with xai's grok imagine image 2.0. text-to-image or editing with up to 5 source images, low or medium quality, 1k or 2k output.

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": "xai/grok-imagine-image-2-0",9    "input": {10      "prompt": "A watercolor painting of a lighthouse at dawn"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": "xai/grok-imagine-image-2-0",8    "input": {9      "prompt": "A watercolor painting of a lighthouse at dawn"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 $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "xai/grok-imagine-image-2-0",7    "input": {8      "prompt": "A watercolor painting of a lighthouse at dawn"9    }10  }' | jq -r '.data.id')1112# later: read its state. done when status is 10 (completed), 11 (failed) or 12 (cancelled)13curl -s https://api.inference.sh/tasks/$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": "xai/grok-imagine-image-2-0",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": "xai/grok-imagine-image-2-0",6    "input": {7        "prompt": "A watercolor painting of a lighthouse at dawn"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 generate, or how to change the source images. with several source images, refer to them as <image_0>, <image_1>, ... in the order given.

example: "A watercolor painting of a lighthouse at dawn"

imagesarray

source images to edit (up to 5, jpeg/png/webp). leave empty to generate from the prompt alone.

qualitystring

'low' is fast and cheaper; 'medium' spends more compute per image for finer detail.

default: "low"

options:"low""medium"

resolutionstring

output resolution. price per image: low 1k $0.04, low 2k $0.06, medium 1k $0.06, medium 2k $0.08.

default: "1k"

options:"1k""2k"

aspect_ratiostring

aspect ratio of the output. 'auto' lets the model choose; when editing it follows the first source image.

default: "auto"

options:"auto""1:1""16:9""9:16""4:3""3:4""3:2""2:3""2:1""1:2""19.5:9""9:19.5""20:9""9:20"

ninteger

number of images to generate (1-10).

default: 1min:1max:10

output

imagesarray*

the generated images. excludes images withheld by xai content moderation.

moderated_countinteger

number of generated images withheld by xai content moderation.

noticestring

set when xai content moderation withheld some or all images.

other image apps

GPT Image 2.6 Flare

openai/gpt-image-2-6-flare

$30.00/M output, $5.00/M text input, $8.00/M image input, $0.10/M SVG input, $0.50/M SVG output

GPT Image 2.6 Sunburst

openai/gpt-image-2-6-sunburst

$30.00/M out, $5.00/M text in, $8.00/M img in; SVG $0.10/$0.50/M in/out

Gemini Nano Banana 2.1

google/gemini-nano-banana-2-1

$1.50/M input, $0.0336–$0.1134/image (1K–4K), +$0.014/query Google Search

GPT Image 2.5 Sunburst

openai/gpt-image-2-5-sunburst

$0.006-$0.21 per 1024x1024 image: low $0.006, medium $0.013, high $0.053, xhigh $0.094, max $0.21. Larger sizes cost more; edits add ~$0.008 per reference image.

GPT Image 2.5 Flare

openai/gpt-image-2-5-flare

$0.006-$0.21/image at 1024x1024: low $0.0059, medium $0.0132, high $0.0527, xhigh $0.0937, max $0.2107. Larger sizes cost more; edits add ~$0.0083 per reference image.

more from xai

Grok Speech to Text

xai/grok-stt

$0.10/hr of audio for files, $0.20/hr for realtime

Grok Imagine Video 1.5

xai/grok-imagine-video-1-5

$0.08/sec 480p, $0.14/sec 720p, $0.25/sec 1080p; $0.01/input image

Grok 4.7

xai/grok-4-7

$2.00/M input, $0.50/M cached, $6.00/M output (2x at 200k+ prompt tokens)

Grok Build 0.1

xai/grok-build-0-1

$1.00/M input, $0.20/M cached, $2.00/M output (2x at 200k+ prompt tokens)

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from the blog

Grok Imagine Image 2.0

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 image apps

more from xai

new models

ready to run Grok Imagine Image 2.0?