import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "inclusionai/ling-3.0-flash-fin", "messages": [ { "role": "user", "content": "Hello!" } ] }, ) print(r.json())
const r = await fetch("https://api.aimlapi.com/v1/chat/completions", { method: "POST", headers: { Authorization: `Bearer ${process.env.AIMLAPI_KEY}`, "Content-Type": "application/json", }, body: JSON.stringify({ "model": "inclusionai/ling-3.0-flash-fin", "messages": [ { "role": "user", "content": "Hello!" } ] }), }); console.log(await r.json());
curl -X POST https://api.aimlapi.com/v1/chat/completions \ -H "Authorization: Bearer $AIMLAPI_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"inclusionai/ling-3.0-flash-fin","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Cached input |
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| Humanity's Last Exam | 22.6% | Expert-level questions across many domains | Source | September 21, 2026 |
| Intelligence | 22.6 | Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial Analysis | Source | September 22, 2026 |
| Coding | 55.6 | Composite score across standardised coding evaluations, measured independently by Artificial Analysis | Source | September 22, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Ling 3.0 Flash Fin This page | Finance-domain reasoning over long documents | |||
| Fast, low-cost reasoning and tool use at scale | ||||
| Reasoning + agents | ||||
| Reasoning + agents | ||||
| Reasoning + agents |
Ling 3.0 Flash Fin is a chat model from inclusionAI. It is the finance-tuned member of the Ling 3.0 Flash line.
It keeps the Flash line's speed-oriented design and adds domain tuning aimed at financial material.
inclusionAI, the AI research group at Ant Group.
Yes, the model supports function calling.
Yes. Responses can be streamed as they are generated rather than returned in one block.
It takes text and returns text.
Send a request to the chat completions endpoint with the model id inclusionai/ling-3.0-flash-fin.