What does an image or a 3D mesh cost to generate?

Q: What does an image or a 3D mesh cost to generate?

price one run, because the ranking reverses between tiers price one image before you plan a batch: on a token-billed route the bill is dominated by the output-token rate, so read the run's own cost rather than reading the input tier and stopping there. and do not sort the catalog by price without checking: one vendor's tiered entries list an amount of zero while billing three cents an image the gap is the tier you read, not a missing rate: the output-token rate of $0.03 per thousand is 97% of what an image costs, and it IS in the catalog next to the input tiers. An earlier version of this page said the listing omitted it. What is inspect-only is the worked low, medium and high examples so budget from a run: the input tier alone is out by a factor of forty on this route, so one call and its own cost field is the reliable estimate and a cheapest-first sort can point at the dearest: one vendor's tiered entries list a price amount of zero in the catalog while billing three cents an image, which puts a vendor 8.6x dearer at the top of a price sort the cheapest vendor is not down: an earlier version of this page said the lowest-listed vendor 502s on every attempt. On a second run it answered first try and billed $0.0035, which is 1.7x below the floor this page quoted status is not success: that 502 run reported its status as COMPLETED with a null output, so check the payload rather than the state

Openai APIs — Monid

What an image actually costs

Say this to your agent

>price one image before you plan a batch: on a token-billed route the bill is dominated by the output-token rate, so read the run's own cost rather than reading the input tier and stopping there. and do not sort the catalog by price without checking: one vendor's tiered entries list an amount of zero while billing three cents an image

What the agent runsdone

openai /v1/image/gpt-image-2$0.005 to $0.03 / 1k tokens0 markup

alibaba /v1/image/qwen-image-3.0$0.003 to $0.03 / image0 markup

minimax /v1/image_generation$0.0035 / result0 markup

What came backone prompt, four sizes · 2026-09-25

What the listing says against what it billedUS dollars for one image

what the run billed$0.006025

what the listing implies$0.000145

the gap is the tier you read, not a missing ratethe output-token rate of $0.03 per thousand is 97% of what an image costs, and it IS in the catalog next to the input tiers. An earlier version of this page said the listing omitted it. What is inspect-only is the worked low, medium and high examples

so budget from a runthe input tier alone is out by a factor of forty on this route, so one call and its own cost field is the reliable estimate

and a cheapest-first sort can point at the dearestone vendor's tiered entries list a price amount of zero in the catalog while billing three cents an image, which puts a vendor 8.6x dearer at the top of a price sort

the cheapest vendor is not downan earlier version of this page said the lowest-listed vendor 502s on every attempt. On a second run it answered first try and billed $0.0035, which is 1.7x below the floor this page quoted

status is not successthat 502 run reported its status as COMPLETED with a null output, so check the payload rather than the state

$0.006025one image, 1024 square

The same prompt on two vendors

Say this to your agent

>generate <prompt> at 1024 by 1024 on two vendors with monid, download both, and tell me the measured pixel dimensions and file sizes from the files themselves rather than from the response

What the agent runsdone

openai /v1/image/gpt-image-2$0.005 to $0.03 / 1k tokens0 markup

alibaba /v1/image/qwen-image-3.0$0.003 to $0.03 / image0 markup

alibaba /v1/image/qwen-image-3.0-pro · not run$0.003 to $0.075 / image0 markup

What came backone prompt, four sizes · 2026-09-25

Same prompt, same 1024 squareUS dollars, and bytes delivered

vendor A · 1,906,937 bytes$0.006025

vendor B · 1,438,205 bytes$0.030000

5.0x on pricethe same prompt at the same requested size cost $0.006025 on one vendor and $0.030000 on the other

and the cheaper one was bigger1,906,937 bytes against 1,438,205 between those two, so the price difference bought no more file. A third and cheaper vendor returned a 288 KB JPEG, so file size does not track price in either direction

the ranking flips at the MIDDLE tierthe flat-price vendor becomes 1.76x cheaper at the medium setting, not the high one. At high the token-billed vendor is about 7x DEARER, so the crossover is earlier and steeper than an earlier version of this page said

the dimensions were honestevery image across every size matched what was asked for on both runs, measured from the file header; note that a size of 4K resolves to a square 4096 rather than UHD, and that only one endpoint accepts that literal at all

$0.036two images, one prompt

Edit an image you already have

Say this to your agent

>edit <image> with openai on monid to <change>. expect the scene to be REGENERATED rather than the pixels preserved: the lighting and framing will shift even where the edit lands correctly, so compare the whole frame, not just the thing you named

What the agent runsdone

openai /v1/image/gpt-image-2-edit$0.005 to $0.03 / 1k tokens0 markup

openai /v1/image/gpt-image-2$0.005 to $0.03 / 1k tokens0 markup

What came backone prompt, four sizes · 2026-09-25

what it didon a second image, asked to recolour a named object, it recoloured that object and added nothing. The regeneration is the reliable part: the lighting and framing moved even though the edit itself was correct

so the risk is drift, not substitutionan earlier version of this page said it adds a new object beside the one you named. That did not reproduce; what reproduced on both runs is that nothing outside the edit is preserved

what it costs$0.014262, which is 2.37x the price of generating a fresh image on the same vendor

so when is it worth itwhen the composition is what you want to keep; if the whole scene is going to be regenerated anyway, a new prompt is cheaper and more direct

the prompt rewrite next doorthe other vendor extends your prompt by default. It is a documented parameter and the response tells you whether a rewrite happened; what it withholds is the rewritten TEXT, so you know it changed and not how

$0.0142622.37x a fresh image

A real 3D mesh

Say this to your agent

>generate a 3d mesh of <subject> with suzanne on monid, asking for glb, obj and stl together in one job rather than one format at a time. do NOT pass the face count the schema prints as its default: that value is rejected upstream and you get a 400. download inside fifteen minutes, or re-mint the link from the download endpoint, which is free

What the agent runsdone

suzanne /v1/generations/text-to-3d$0.800 markup

suzanne /v1/generations/photo-to-3d$0.800 markup

What came backone prompt, four sizes · 2026-09-25

What $0.80 and 151 seconds producedthe parsed GLB

triangles493,418

vertices262,710

embedded PBR textures3

it is realabout sixteen megabytes that parse as valid glTF 2.0, UV unwrapped, with exactly three embedded PBR textures, on both subjects tried, usable as it comes rather than as a starting point

the clock is shortnine hundred seconds on that link, confirmed in the payload, the tightest expiry in either aisle, so download inside the same run

all three formats come in one joban earlier version of this page said asking for OBJ or STL returns a 404, that no converter exists and that another format is another $0.80. All three are wrong: the outputs parameter takes glb, obj and stl together, the schema says outright that OBJ and STL are converted from the GLB, and one $0.80 run returned all three

and the expiry is not a deadlinethe download endpoint re-mints a fresh fifteen-minute link for $0.00, so a missed window costs a round trip rather than the job

the documented default is rejectedthe face-count parameter prints a default in its own schema that the provider refuses; the values it accepts are a short list well above it, so following inspect literally returns a 400

and it takes time151.4 seconds, which is long enough that a job runner needs to expect it rather than time out

$0.80one mesh, 151 seconds

A hundred images

Say this to your agent

>work out what a hundred images costs on each route at the tier i actually need, not at the cheapest tier. the ranking between vendors reverses between the low and the high setting

What the agent runsdone

openai /v1/image/gpt-image-2$0.005 to $0.03 / 1k tokens0 markup

alibaba /v1/image/qwen-image-3.0$0.003 to $0.03 / image0 markup

alibaba /v1/image/qwen-image-3.0-pro · not run$0.003 to $0.075 / image0 markup

What came backone prompt, four sizes · 2026-09-25

A hundred imagesUS dollars

cheapest vendor$0.35

flat-price vendor, any size$3.00

top tier on the other$7.50

the range is wider than this page first measureda hundred images ran $0.35 at the cheapest vendor and about $21 at the dearest tier, against the $0.60 to $7.50 an earlier version quoted. The point is the span, not the endpoints: price the tier you actually need

where it crossesat the MIDDLE quality setting of the token-billed vendor. Below it the token-billed one is 5.0x cheaper; at medium the flat-price one is 1.76x cheaper; at high the token-billed one is about 7x dearer

the flat-rate bargainone vendor charges the same $0.030 whether you ask for 1024 square or 2048 square, so at large sizes it is the cheap option rather than the dear one

count the images you getasking for two returns one entry with both images inside a content array, so iterating the entries drops one you paid for

$0.00arithmetic on measured rates

What these two aisles cannot do

Say this to your agent

>before you design a pipeline, tell me what is genuinely missing and what merely needs a step: vector output and rigging are absent, transparency is a parameter on the image endpoints rather than a separate remover, and a generated image reaches the mesh generator by downloading it and putting it through the upload endpoint. check each one against the schema rather than against a capability search

What the agent runsdone

suzanne /v1/generations/photo-to-3d$0.800 markup

openai /v1/image/gpt-image-2$0.005 to $0.03 / 1k tokens0 markup

suzanne /v1/generations/text-to-3d$0.800 markup

What came backone prompt, four sizes · 2026-09-25

the two aisles DO connect, for $0.015an earlier version of this page said there is no path from a generated image to a mesh. There is: an upload endpoint takes the file and hands back the id the photo-to-3D call wants, confirmed end to end with a generated PNG. The honest sentence is download and re-upload for a cent and a half, not that it cannot be done

and transparency is a parameterevery endpoint on one vendor takes a transparent background directly, so a separate background remover is not something this aisle is missing

what is genuinely absentvector output and rigging. There is no upscaler either, though one endpoint re-renders to 4K, which covers some of what a reader wants an upscaler for

and it is not PNG onlythirteen image endpoints rather than eleven, and one returns JPEG over a plain http url

what discover actually doesit scores about 0.79 for upscale and for remove background, and on a second look both of those hits can do the job asked of them, so the warning is to open the schema rather than that the results are junk

$0.00know the holes first

Openai

How-to guide

Set up Monid.

Pick what you need. Say it in one sentence.

What an image actually costs

The same prompt on two vendors

Edit an image you already have

A real 3D mesh

A hundred images

What these two aisles cannot do

Read more

MiniMax H3 Max on Monid

LLM gateway or MCP gateway

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