Ling 3.0 Flash VL overview
Ling 3.0 Flash VL specs
- Model ID
inclusionai/ling-3.0-flash-vl- Developer
- inclusionAI
- Context window
- 131,072 tokens
- Max output
- 32,768 tokens
- Input
- Image, Text, Video
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
What is Ling 3.0 Flash VL API?
Ling 3.0 Flash VL is the vision-language member of inclusionAI's Ling 3.0 Flash family. It keeps the speed and low cost of the text-only Flash models while accepting image, video and text input, returning text output.
It ships with a 131,072-token context window and up to 32,768 output tokens, and supports reasoning, streaming responses, structured output and tool/function calling.
Document and screenshot understanding
Read charts, tables, UI screenshots and scanned pages, and return structured output that downstream code can consume directly.
Video summarisation
Accepts video input alongside text, making it suitable for clip-level description, tagging and summarisation tasks.
Tool-using visual agents
Function calling plus vision lets the model inspect an image and then call an external tool with structured arguments in the same turn.
Use cases
Visual document analysis: the model is documented as handling object counting, complex layouts, charts, and document content, making it suited to reading and analyzing visual documents.
Visual reasoning and verification: it is documented for calculation, multi-step reasoning, and external information verification using visual evidence.
Web and software interface automation: it is documented as able to understand web and software interfaces and translate that visual information into sequences of actions.
Video understanding tasks: it is documented as supporting video understanding, including event localization, long-video question answering, and video clip editing.
Capabilities
- Reasoning
- Streaming
- Structured outputs
- Function calling
- Vision
Ling 3.0 Flash VL benchmarks by 
Artificial Analysis
See how Ling 3.0 Flash VL scores on independent evaluations. Data retrieved Nov 3, 2026.
Benchmark results
Compare 14 models available on AI/ML API across 5 independent benchmarks.
Humanity's Last Exam
Expert-written questions across academic subjects.
GPQA Diamond
Graduate-level science questions written to resist web search.
Terminal-Bench 4.0
Agentic tasks completed in a command-line environment.
AA-LCR
Reasoning across long documents of about 100k tokens.
SciCode
Python coding tasks drawn from scientific research.
Ling 3.0 Flash VL API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $0.0635 | 1M tokens |
| Output | $0.1904 | 1M tokens |
| Cached input | $0.0127 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
Ling 3.0 Flash VL vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
 Ling 3.0 Flash VL | $0.0635 | $0.1904 |
 Hy-MT2-1.8B | $0.0466 | $0.1873 |
 Laguna S 2.1 | $0.0952 | $0.1904 |
 GPT OSS 20B | $0.05 | $0.2 |
| Ling-3.0-flash | $0.0794 | $0.2328 |
How to use the Ling 3.0 Flash VL API
View docs
Build with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "inclusionai/ling-3.0-flash-vl",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "inclusionai/ling-3.0-flash-vl",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = 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-vl",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to Ling 3.0 Flash VL
Ling 3.0 Flash VL FAQ
How much does Ling 3.0 Flash VL cost?
Ling 3.0 Flash VL costs $0.0635 input and $0.1904 output per 1M tokens on AI/ML API, billed as you go with no subscription.
What is Ling 3.0 Flash VL?
Ling 3.0 Flash VL is the vision-language member of inclusionAI's Ling 3.0 Flash line: a fast, low-cost chat model that accepts image, video and text input and returns text.
How does Ling 3.0 Flash VL differ from Ling 3.0 Flash?
It keeps the Flash line's speed-oriented design and adds visual understanding. Ling 3.0 Flash takes text only; the VL variant also accepts images and video.
Who builds Ling 3.0 Flash VL?
inclusionAI, the AI research group at Ant Group.
What inputs and outputs does Ling 3.0 Flash VL support?
It takes image, video and text input and returns text.
How large is the context window?
131,072 tokens, with up to 32,768 tokens of output.
Does Ling 3.0 Flash VL support tool calling?
Yes, it supports function calling and structured outputs, alongside streaming responses and reasoning.
What is Ling 3.0 Flash VL best suited for?
High-volume multimodal work where per-request cost matters: document and screenshot understanding, image and video captioning, tagging and moderation pipelines.
Is there a shorter model name I can use?
Yes. The model also answers to the alias ling-3.0-flash-vl.
How do I call Ling 3.0 Flash VL on AI/ML API?
Send a request to the chat completions endpoint with the model id inclusionai/ling-3.0-flash-vl. The request shape is the same as for any other chat model on AI/ML API.