import requests r = requests.post( "https://api.aimlapi.com/v1/chat/completions", headers={"Authorization": "Bearer " + AIMLAPI_KEY}, json={ "model": "inclusionai/ling-3.0-flash", "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", "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","messages":[{"role":"user","content":"Hello!"}]}'
OpenAI-compatible — swap the base URL and it works with your existing SDK.
| Type | Price |
|---|---|
| Input | |
| Output | |
| Cached input |
A free-tier alias (ling-3.0-flash:free) is also available.
| Benchmark | Score | What it measures | Source | Retrieved |
|---|---|---|---|---|
| Intelligence | 24.9 | Composite score across standardised reasoning, knowledge and problem-solving evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Coding | 50.6 | Composite score across standardised coding evaluations, measured independently by Artificial Analysis | Source | September 12, 2026 |
| Model | Input | Output | Context | Best for |
|---|---|---|---|---|
Ling-3.0-flash This page | Fast, low-cost reasoning and tool use at scale | |||
| Reasoning + agents | ||||
| Reasoning + agents | ||||
| Reasoning + agents | ||||
| Reasoning + agents |
Ling-3.0-flash has a 262,144 tokens context window and can return up to 32,768 tokens.
Ling-3.0-flash takes text as input and returns text.
Use inclusionai/ling-3.0-flash as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Ling-3.0-flash became available on July 23, 2026.
Ling-3.0-flash is priced at input $0.103155 / 1M tokens, output $0.302588 / 1M tokens, cached input $0.020631 / 1M tokens.
Yes, Ling-3.0-flash can stream responses as they are generated.
Ling-3.0-flash was built by inclusionAI.
It supports reasoning, streaming, and function calling, making it suitable for chat-based tasks that need tool use.