Ant Ling launched Ling-3.2-flash on November 5 with a two-week introductory free period.[1] Developers evaluating multimodal APIs can use the trial to test chart reading, interface analysis and information retrieval on their own work.

The model accepts text, images and video, with a listed context window of one million tokens.[2] Lengthy documents and mixed-format material are useful starting points. Track how accurately it extracts the details you need and how much time people spend reviewing its answers.

Pricing and the free period

The official pricing page says charging resumes after the introductory offer. As of publication, it lists neither a specific Ling-3.2-flash tariff nor an exact cutoff time or time zone.[3] Access through another provider is subject to that provider's pricing and promotion terms.

Keep a way to switch back to your current model and monitor usage during the trial. Record input and output usage and the number of retries for each task so you can estimate costs once regular pricing is available.

Try three kinds of work

Start with a document that mixes charts and prose. Ask the model to extract a few figures and identify the page or chart supporting each answer. Check the numbers, units and dates, and note any confusion between chart labels and the surrounding explanation.

Next, try an interface screenshot. Ask for the visible components, text and relative positions, including anything the image leaves unclear. If you then ask it to generate or modify code, run the resulting page and compare the layout and behavior with the intended result.

Finally, test retrieval across a long document. Place relevant details near the beginning, middle and end, and include questions that require checking more than one section. Add a few questions the material cannot answer to see whether the model identifies the missing information.

Use public material or content you have permission to upload. Remove personal or confidential details where needed, and keep the same inputs and reference answers when comparing models.

API integration and rate limits

The official quickstart uses the OpenAI SDK with https://api.ant-ling.com/v1/ as the base URL and Ling-3.2-flash as the model name.[4] Get a short text request working first, then add images, longer inputs and batch processing in stages. This makes failures easier to isolate.

The current limits page specifies two requests per second and a 90-second timeout for synchronous calls, and recommends streaming.[5] Queue batch requests and use backoff for rate-limit errors. Measure total turnaround time, including waiting, retries and human review.

Compare the trial with your current workflow

For a small set of representative tasks, save the input, reference answer, error category and total processing time. Run the same tasks through your existing workflow. Once regular pricing is clear, compare API charges alongside the cost of review and corrections to decide whether to switch.

This article draws on official documentation; it does not report hands-on performance tests.