Speed
Output tokens / second
Custom pricing for production workloads
Gemini 2.5 Flash Lite Preview is a lightweight AI model developed by Google, optimized for quick responses and efficient processing, making it ideal for tasks requiring minimal latency and resource consumption
google/gemini-2.5-flash-litehttps://api.aimlapi.com/v1What is Gemini 2.5 Flash Lite Preview API?
Gemini 2.5 Flash Lite Preview is a lightweight AI model developed by Google, optimized for quick responses and efficient processing, making it ideal for tasks requiring minimal latency and resource consumption
Where to Use Gemini 2.5 Flash Lite Preview
Coding and code review
Generate, debug, and review code across languages, reading whole files or repos in a single prompt.
Gemini 2.5 Flash-Lite is documented as suited for high-volume classification tasks, where fast, low-cost handling of many requests is the priority. It is also suited for simple data extraction, especially when the input is lightweight and the output needs to be structured. Another documented use case is translation, including high-throughput translation workflows. It is also positioned for intelligent routing and other cost-sensitive, high-scale operations.
See how Gemini 2.5 Flash Lite Preview compares in generation speed and latency. Data retrieved Nov 3, 2026.
Output tokens / second
Compare 14 models available on AI/ML API across 5 independent benchmarks.
Expert-written questions across academic subjects.
Graduate-level science questions written to resist web search.
Reasoning across long documents of about 100k tokens.
Following precise instructions about the shape of the answer.
Customer support agent tasks with tool calls.
| Usage | Price | Unit |
|---|---|---|
| Input | $0.075 | 1M tokens |
| Output | $0.3 | 1M tokens |
| Cached input | $0.075 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
| $0.075 | $0.3 | |
| $0.3 | $2.5 | |
| $0.75 | $3.75 | |
| $0.75 | $3.75 | |
| $2 | $10 |
Give your agent the model details, code and documentation.
export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "google/gemini-2.5-flash-lite",
"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": "google/gemini-2.5-flash-lite",
"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": "google/gemini-2.5-flash-lite",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Gemini 2.5 Flash Lite Preview has a 1,000,000 tokens context window and can return up to 1,048,576 tokens.
Gemini 2.5 Flash Lite Preview takes image, text as input and returns text.
Use google/gemini-2.5-flash-lite as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
Gemini 2.5 Flash Lite Preview costs $0.075 input and $0.3 output per 1M tokens on AI/ML API, billed as you go with no subscription.
Yes, Gemini 2.5 Flash Lite Preview can stream responses as they are generated.
Yes, Gemini 2.5 Flash Lite Preview accepts image input alongside text.
Gemini 2.5 Flash Lite Preview was built by Google.
It is designed for quick responses and efficient processing, suited for tasks that need minimal latency and low resource use.
It is optimized for both low latency and efficient, cost-conscious processing.