Updates that matter when you build

403 example runs now cover 117 of the 120 callable endpoints. Each one is a job actually run on this platform — not a concept image, not a still borrowed from a model card — and each carries three things:

• The finished file, served from our own CDN at its original aspect ratio.
• The complete input object that produced it — prompt, size, duration, every parameter — ready to copy straight into your own call.
• A note in all ten interface languages explaining why that input was chosen: which aspect ratio the composition was written for, which parameter is doing the work, what to change first.

They appear on each model page as a wall of results you can scan, and come back from the API on GET /console/v1/catalog/models/{slug} under examples.

Choosing a model used to mean reading a parameter table and guessing what it would look like. Now you can see what an endpoint actually produces, and start from an input that is known to work on it.

Browse the catalogue

Six endpoints join the swap family, three of them for video. What separates them is how much actually travels.

Images

• spicyapi/face-swap-pro-v1/edit — only the facial features move. The target's hairstyle, hairline, head silhouette, pose, wardrobe, lighting and background all stay as they were. $0.16 per image.
• spicyapi/face-swap-v1-plus/edit — moves the face and reconciles skin tone between the two images as part of the transfer; the engine blends either the face alone or the whole head, whichever reads better. $0.16 per image.
• The original spicyapi/face-swap-v1/edit and spicyapi/head-swap-v1/edit stay at $0.013 per image.

Video

• spicyapi/face-swap-video-v1/video-edit — carries the features from a single reference image through every frame. The performer's hairstyle, head silhouette, movement, wardrobe and lighting are untouched. $0.0325 per output second.
• spicyapi/head-swap-video-v1/video-edit — hair, head shape and identity change. $0.064 per output second.
• spicyapi/character-swap-v1/video-edit — the whole figure changes, clothing included. $0.064 per output second.

The two multi-person video endpoints are deliberately two-step. Call the matching video-analyze endpoint first, at $0.08 per request: it follows every person it can see through the clip and returns one preview still each, in a fixed order — the first image is position 0, the second is position 1. You then pass the positions you picked, with one to three reference photos for each. Nothing is left to guess about which person the model will act on.

Three xAI models, one chat endpoint each, all speaking the OpenAI wire format with streaming.

• 40% below xAI's own published price, on every tier, checked against their pricing page on 19 September 2026.
• Only 4.3 accepts reasoning_effort: none. On 4.5 and 4.6 that value is refused upstream — the other four levels work on all three.
• 4.5 caches more cheaply than 4.6 ($0.18 against $0.30 per 1M cached input tokens) while matching it everywhere else.
• Prompts of 200,000 tokens or more bill at a higher long-context rate, exactly as xAI does. Reasoning tokens count toward max_tokens, so budget for them.
• These routes take text and images. They do not accept file or PDF parts.

Five image endpoints, spanning a 4x price range, so you can match the tier to the job rather than paying top rate for a thumbnail.

• bytedance/seedream-4.0/text-to-image and bytedance/seedream-4.0/edit — $0.03 per image, both Uncensored. The edit endpoint takes an existing image and a written instruction.
• krea/2-large/text-to-image — $0.06 per image, Filtered.
• krea/2-medium/text-to-image — $0.03 per image, Softened.
• krea/2-medium-turbo/text-to-image — $0.015 per image, Filtered. The cheapest image endpoint in the catalogue after the swap family.

Two things worth knowing before you pick one. The Krea tiers differ in what they will accept, not only in price: Filtered refuses mature requests outright, while Softened returns a toned-down result and still bills for it — so on a Softened route, check the output rather than the status code. And image size is not a modifier applied after the fact: the example runs on each model page show the exact size each composition was written for, because a prompt built for a tall frame does not simply resize into a wide one.

heartmula/transcribe/speech-to-text transcribes the sung lyrics in an audio file and returns them as text on the task. It is tuned for vocals over music rather than for plain speech.

• One input: audio_url, which must resolve directly to an audio file. There is nothing else to send — no language hint, no timestamp request, no diarisation switch.
• The result is text on the task. No media asset is produced, so there is no file to download and nothing enters media retention.
• No line timings, no confidence values, no speaker labels.
• $0.05 per transcription, regardless of how long the audio is.

It is also the first endpoint in the catalogue whose output is text rather than a file. If your integration assumes every completed task carries a downloadable asset, this is the one that will find that assumption — worth a look at your result handler before you wire it in.