Google: Veo 3.1 Fast

Google: Veo 3.1 Fast is a video generation model from Google, positioned as the mid-tier option in the Veo 3.1 line. It is built to balance speed and quality, offering faster turnaround than the full Veo 3.1 model while still producing high-quality output. If you are already working within Google's ecosystem of generative media models, this is the variant aimed at workloads where iteration speed matters more than maximum fidelity.

The model accepts text and image inputs and returns video as its only output. It generates native synchronized audio alongside the visuals, so you do not need a separate audio pipeline for speech, sound effects or ambient sound. Output can be rendered at 720p, 1080p or 4K, in either 16:9 or 9:16 aspect ratio, with durations of 4, 6 or 8 seconds. For image-driven work, you can supply a first frame, a last frame, or both, which gives you control over how a shot begins and ends. No context window is published for this model, which is expected for a video generator rather than a text model.

Those capabilities point to a fairly specific set of uses. Short 16:9 clips at 4K suit advertising spots, product teasers and social pre-rolls, while the 9:16 option covers vertical formats for stories and short-form feeds. Because audio is generated natively, the model fits explainer clips, dialogue-driven scenes and any content where sound needs to line up with the picture without manual mixing. First and last frame conditioning is useful for animating a still image, bridging two keyframes, or producing consistent shot transitions in a longer edit. The 4, 6 and 8 second durations keep individual generations short, so the model works best as a shot-level tool rather than a single-pass long-form generator.

You call it through api14's OpenAI-compatible API using the model id "google/veo-3.1-fast". The supported request parameters are max_tokens, response_format, seed, temperature and top_p. Seed is worth setting when you want reproducible generations across runs, and temperature and top_p give you control over how much variation the model introduces. Because the interface follows the OpenAI schema, existing clients and SDKs generally work with minimal changes.

There are a few things to keep in mind when choosing this model. Context length is not published, and maxOutput is listed as 0, so do not plan around a documented token budget for output. If your priority is the highest possible quality rather than turnaround time, the full Veo 3.1 model is the more appropriate choice, since Fast is explicitly the speed-oriented tier. Clip length is capped at 8 seconds, so longer sequences need to be assembled from multiple generations.