ByteDance Seed: Seed 1.6 Flash

ByteDance Seed: Seed 1.6 Flash is a text-focused multimodal model from ByteDance Seed, the AI research arm of ByteDance. It was released by the provider on 23 December 2025 and sits in the text category on api14, meaning its output is text even though it accepts more than text as input. If you are already working with ByteDance models or want a fast multimodal option from that family, this is the model id to look for.

On the input side, Seed 1.6 Flash accepts images, text and video, and it returns text. That combination makes it a multimodal deep thinking model rather than a plain text generator, so you can send a screenshot, a document image or a video clip alongside your instructions and get a written answer back. The context window is 262,144 tokens, which is large enough to hold long documents, extended conversation histories or sizeable media-derived prompts in a single request. The maximum output is 32,768 tokens, so responses can be long when the task calls for it. Reasoning support is exposed through the reasoning and include_reasoning parameters, which is consistent with the deep thinking description.

Those capabilities point to a few practical patterns. Visual understanding plus a 256k context suits tasks where you need to reason over a mix of material: analysing a long report with embedded charts, summarising or extracting structured data from video, answering questions about screenshots or diagrams, or building assistants that take image and text input in the same call. The large output ceiling helps for long-form generation such as detailed summaries, multi-section write-ups or structured JSON that would otherwise be truncated. Tool calling and structured outputs also make it usable as the reasoning step inside an agent or pipeline that needs to return machine-readable results.

You call it through api14's OpenAI-compatible API using the model id "bytedance-seed/seed-1.6-flash". Because the interface follows the OpenAI format, existing SDKs and clients generally work with only the base URL and key changed. The supported request parameters are frequency_penalty, include_reasoning, max_tokens, reasoning, response_format, stop, structured_outputs, temperature, tool_choice, tools and top_p. Note that presence_penalty is not in that list, so do not rely on it. Use max_tokens to cap output, temperature and top_p to tune sampling, and tools with tool_choice when you want the model to call functions.

Keep the limits in mind when choosing. Output is text only, so if you need generated images or audio, this model is not the right fit. It is a Flash variant, which suggests a speed-oriented option in the Seed line, so for workloads where the deepest possible reasoning matters more than latency, a larger sibling model may be worth comparing. Otherwise, for multimodal input, long context and tool-driven workflows, it covers a wide range of developer use cases.