Grok Imagine Image Quality
grok-imagine-image-quality by xAI: billed per media unit (second, image or minute of audio). Call it through the odnoga LLM gateway; see the pricing page for the media rate.
grok-imagine-image-quality is served by xAI and called through odnoga on /v1/images/generations, in the same OpenAI-compatible shape every other model on that endpoint uses. It accepts images alongside text.
Specification and price
| Vendor | xAI |
|---|---|
| Model ID | grok-imagine-image-quality |
| Served on | /v1/images/generations |
| Pricing | Per media unit (second / image / minute) — see pricing |
| Capabilities | Reads images, Prompt caching, Batch |
Vendor cost is the list rate for this model as recorded in the odnoga catalog — per second, image or minute, not per token; your price applies your plan margin with the same formula that bills every request — see pricing. Pricing
Call it through odnoga
const res = await fetch("https://api.odnoga.com/v1/images/generations", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.ODNOGA_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "grok-imagine-image-quality",
prompt: "A red bicycle against a white wall",
n: 1,
size: "1024x1024",
}),
});
One endpoint, one key, one bill — /v1/images/generations takes the same shape whichever vendor is behind it. Swap the model id and odnoga handles keys, routing, limits and cost accounting.
What grok-imagine-image-quality can do
Everything below is what the model itself supports. Ask for something it does not do and odnoga tells you before the request reaches the provider, instead of returning a worse answer.
Send a screenshot, a photo or a scan in the same message as your text.
A prompt you send repeatedly is charged at the cached rate, which is a fraction of the input price.
Work that can wait goes through at a lower price.
Beyond text
Produces pictures rather than describing them.
How to use grok-imagine-image-quality
Derived from the odnoga catalog record for this model.
Best for
- Generating and editing images from a text prompt, billed per image rather than per token.
Not the right pick when
- Agent loops that must call your functions — tool calling is not available here.
- Pipelines that require guaranteed JSON — parse defensively or pick a model with enforced JSON.
- Large documents in one request — the window is 8K tokens, so you will need chunking.
- Anything where a wrong answer is costly without a human check — no model in the catalog removes that requirement.
Practical tips through odnoga
- 01Pin the model id in a managed prompt version, so a model swap is a version change you can compare and roll back, not an edit in application code.
- 02Compare it against 2–8 other models on the same frozen test cases in the evaluation laboratory before you make it the production default.
- 03For repeated identical deterministic calls, odnoga answer reuse returns the stored answer and bills no vendor tokens — turn it off for creative output.
- 04Set a fallback model on the route so a vendor incident degrades quality instead of returning an error, and a per-tenant budget so one caller cannot spend the month.
If grok-imagine-image-quality is not the one
Models that take the same kind of input, are priced the same way, and do the closest thing to what this one does. Not a quality ranking — odnoga does not benchmark models.
| Model | Context | Input / 1M | Output / 1M | Capabilities |
|---|---|---|---|---|
| grok-imagine-image-quality | 8K | — | — | Reads images, Prompt caching, Batch |
| grok-imagine-image | 8K | — | — | Reads images, Prompt caching, Batch |
Questions
- How much does grok-imagine-image-quality cost per 1M tokens?
- xAI lists — / — per 1M input / output tokens in the odnoga catalog. Through odnoga you pay that vendor price plus your plan margin, and every request is recorded with both numbers.
- What is grok-imagine-image-quality best for?
- Generating and editing images from a text prompt, billed per image rather than per token.
- Can I switch to grok-imagine-image-quality without changing my code?
- Yes. odnoga exposes one OpenAI-compatible endpoint, so switching means sending "grok-imagine-image-quality" as the model id — or changing it in the managed prompt version, with no application deploy.
- How large is the grok-imagine-image-quality context window?
- 8K tokens of input.
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