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AI Image & Video API Guides
Hands-on model tests, production tutorials, prompt techniques, and current API pricing for generative media teams.
GPT Image 2.5 Flare vs Sunburst: Choosing a Product Poster
The same blue kettle becomes a kitchen product image and an AER HOME brand poster, showing how use changes the visual choice. The kitchen images are overall close; the useful distinctions are product scale, quiet space, light, and props. The posters differ more clearly: one is a clean blue geometric ad, while the other combines a black-and-blue headline with kitchen details.
GPT Image 2.5 vs Seedream 5.0 Pro: Products & Posters
Flare makes the earbud product more direct and prominent, while Seedream adds a side-on photographic mood. Both posters render the main Chinese copy correctly, but Seedream adds a flower that may change a minimalist brand image. Start with Flare for quick product and event recognition; consider Seedream for paper texture and a softer atmosphere.
GPT Image 2.5 vs FLUX.2 Pro: Which Looks Better?
Sunburst keeps the watch dial easier to read, while FLUX.2 Pro makes the glass reflection more pronounced. Sunburst places the linen-bag label more coherently; FLUX.2 Pro needs a label correction. Choose clear detail for a product page, or use FLUX.2 Pro’s wider composition as a reference for banners and collections.
Best AI for E-commerce Product Images: A Comparison
For the bedroom scenes, Flare best fits the right-product, left-copy layout; Seedream feels more lived-in, while FLUX adds warmth but moves the lamp left and adds a cable. All three posters place the lamp on the right; Flare is easiest to continue designing, Seedream is softer, and FLUX has an extra full stop plus a malformed first subtitle glyph. Choose separately for the listing, lifestyle scene, and campaign poster so each image has a clear job.
How to Use gpt-image-2.5-flare via the hiapi API
A hands-on guide to gpt-image-2.5-flare, hiapi's unified text-to-image and image-editing model, covering the async task API, a full Node.js example, and production patterns like callbacks and idempotency keys.
How to Use the minimax-h3-max API: curl, Python, and a Working Request
minimax-h3-max is a text-to-video model on hiapi's async /v1/tasks endpoint, not a chat model despite the name. Confirmed input fields: prompt (required), duration (int seconds), resolution ('480P'|'768P'), aspect_ratio (6-way enum). No working image-input field exists for this model. Production pattern: swap polling for callback.url + when:'final', and set an Idempotency-Key header so retried requests don't double-bill. Auth failures return 401 with error.code='permission_denied'; invalid fields return 400 with error_code='INVALID_REQUEST'.
How to Use gpt-image-2.5-sunburst via the hiapi API: curl, Python, and a Working Request
gpt-image-2.5-sunburst handles both text-to-image and image editing through one model id on POST /v1/tasks. Only `prompt` is required; `image_urls`, `aspect_ratio`, `quality`, `background`, and `output_format` all have defaults. Use a callback with when:"final" instead of polling in production, and store your own idempotency key before submitting. Auth failures return HTTP 401 with error_code permission_denied, separate from task-level success/failed states.
GPT Image 2.5 Flare Prompts: Copy-Paste Recipes With Real Outputs
Structured, single-purpose prompts outperform long adjective lists on Flare. Catalog shots need named background material, light direction, and camera angle — not just "white background." Background edits require an explicit "keep the product unchanged" instruction or the product itself drifts. Flare renders non-English text (tested: Chinese) accurately enough for production, with mandatory human review. A one-sentence prompt can beat an over-engineered one for editorial shots — Flare's defaults are strong.
GPT Image 2.5 vs Nano Banana 2: 9 Real Outputs
Both Image 2.5 models followed the two-stone requirement; Nano Banana 2 added a third stone. All three rendered the main Chinese poster copy correctly, but generated orange slices instead of peel. All three changed the shared image background; Nano Banana 2 changed the bottle color more noticeably.
Using gpt-6-astra for e-commerce product images via the hiapi API
GPT-6 Astra is a text-only reasoning model — it can't generate the product photos, but it can generate everything written around them. Use JSON schema output on the Responses API to turn spec sheets into structured, ready-to-publish listing copy at scale. Build a store=false support assistant by replaying conversation history yourself, with function calls for order lookups. Standard pricing is $2.50/1M input and $12.50/1M output tokens; crossing 272,000 input tokens per request switches the whole call to the long-context tier. Pair this with an image model like GPT Image 2 for the visual side of the same product listing.
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