ByteDance Seed: Seedream 5.0 Flash

Seedream 5.0 Flash is an image generation and editing model from ByteDance Seed. It belongs to the Seedream 5.0 family, where it sits as the fast, cost-efficient tier, positioned for high-volume production and interactive workloads rather than for cases where the largest model in the family is required.

The model is an image model. It accepts text and image input, and its output is an image. That combination of input modalities is what makes both generation from a written prompt and editing of existing images possible within the same model. It supports up to 14 input references, so a request can be guided by multiple source images rather than a single one. There is no text output, which means the model returns images rather than written descriptions or answers. No context length is published for this model, so token based planning around a context window is not applicable here. The request parameters listed for it are frequency_penalty, max_tokens, temperature and top_p.

Because the input side covers both text and images and the output is always an image, the practical uses follow from generating and editing visuals at volume. Text and image prompts together suit product imagery, marketing and social assets, concept and draft visuals, and variations on an existing image where the source images carry the look you want to keep. The reference inputs are useful when a brief needs to stay visually anchored to supplied material. Since the model takes prompts and reference images and returns images, it fits pipelines that need many images quickly, including interactive tools where a user adjusts a prompt and expects a result in the same session.

You call the model through api14's OpenAI-compatible API using the model id "bytedance-seed/seedream-5-0-flash". Requests are built the same way as other OpenAI-compatible calls, with that id as the model value and text and image input supplied the way the endpoint expects. The supported request parameters are frequency_penalty, max_tokens, temperature and top_p. On top of those, the image settings are resolution, aspect_ratio, n, input_references and seed. Resolution is an enum of 1K or 2K. aspect_ratio is an enum covering 1:1, 1:2, 2:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 9:19.5, 19.5:9, 9:20, 20:9, 9:21, 21:9 and auto. n accepts a single value only, with a minimum of 1 and a maximum of 1, so one image per request. input_references ranges from 0 to 14, and seed is a boolean.

Worth knowing before you commit: n is fixed at 1 and cannot be raised to a higher count, so you issue a separate request for each image you want. The model outputs images only, so any task needing text output, such as classification or summarisation, needs a different model. Both resolution options top out at 2K, which may be a constraint if you need larger renders from the model itself. Long context reasoning is not something this model does. If your workload is primarily text, or you need a single call to return multiple images, another model on api14 is likely a better fit.