Text GenerationGoogle
Gemini 2.5 Flash Lite API
Google Gemini 2.5 Flash Lite — ultra-low-cost, low-latency model for high-volume everyday tasks.
24H Status Monitor
24h success rate: 86%
Model:
Price: 0.2 credits per 1K input tokens · ≈ $0.0001-$0.0002 · 0.3 credits per 1K output tokens · ≈ $0.0001-$0.0003High stability with detailed usage records on the APIAny platform.
gemini-2.5-flash-lite
40 (suggested: 2,000)
0.7
02
Sampling temperature.
4096
165536
Maximum output tokens.
USD estimate $0.001-$0.002: highest recharge package uses $1 = 2,000 credits; entry package uses $1 = 1,000 credits.
Preview
No Task RunningLLMResult preview
History
Saved locally in this browser
0 running · 0 completed
Your generation history will appear here
Input
0.2 credits/1K
≈ $0.0001-$0.0002
Output
0.3 credits/1K
≈ $0.0001-$0.0003
Cache
0.02 credits/1K
≈ $0.00001-$0.00002
Context
1M
Max output
66k
Pricing
Model ID
Type
Quality
Price
gemini-2.5-flash-lite
Text Generation
Input tokens
0.2 credits per 1K input tokens · ≈ $0.0001-$0.0002
gemini-2.5-flash-lite
Text Generation
Cache read tokens
0.02 credits per 1K cached input tokens · ≈ $0.00001-$0.00002
gemini-2.5-flash-lite
Text Generation
Output tokens
0.3 credits per 1K output tokens · ≈ $0.0001-$0.0003
gemini-2.5-flash-lite
Text Generation
Minimum request
0.02 credits minimum · ≈ $0.000012-$0.000024
Model IDgemini-2.5-flash-lite
TypeText Generation
QualityInput tokens
Price0.2 credits per 1K input tokens · ≈ $0.0001-$0.0002
Model IDgemini-2.5-flash-lite
TypeText Generation
QualityCache read tokens
Price0.02 credits per 1K cached input tokens · ≈ $0.00001-$0.00002
Model IDgemini-2.5-flash-lite
TypeText Generation
QualityOutput tokens
Price0.3 credits per 1K output tokens · ≈ $0.0001-$0.0003
Model IDgemini-2.5-flash-lite
TypeText Generation
QualityMinimum request
Price0.02 credits minimum · ≈ $0.000012-$0.000024
API
curl /v1/chat/completions \
-H "Authorization: Bearer sk-your-api-key" \
-H "Content-Type: application/json" \
-d '{
"model": "gemini-2.5-flash-lite",
"messages": [
{
"role": "user",
"content": "用三句话介绍 APIAny.AI 的多通道模型聚合能力，并给出一个生产环境建议。"
}
],
"temperature": 0.7,
"max_tokens": 4096
}'
