Google's smallest and most cost-effective 2.5 model, built for at-scale usage. Built by Google.
Prices updated
Input price
$0.10
per 1M tokens · Standard
Output price
$0.40
per 1M tokens · Standard
Input limit
1M
tokens
Output limit
66K
tokens
Input formats
Output formats
Gemini 2.5 Flash-Lite price history
2 price records since 9/25/2026
Gemini 2.5 Flash-Lite cost calculator
$4.00/month
Standard pricing
Overview
What is Gemini 2.5 Flash-Lite?
Gemini 2.5 Flash-Lite is a text & reasoning and vision model from Google. Google's smallest and most cost-effective 2.5 model, built for at-scale usage. Its 1M context window and $0.10 input price make it a candidate for cost-sensitive, high-throughput applications.
Benchmarks
Gemini 2.5 Flash-Lite benchmarks & speed
How Gemini 2.5 Flash-Lite scores on standardized evaluations, and where it lands among every model we track.
6.7
Intelligence Index
268tok/s
Output speed
Reasoning
GPQA Diamond
47.4%
Graduate-level scientific reasoning · top 89%
HLE
3.7%
Humanity's Last Exam · top 93%
Latency & design
- Time to first token
- 0.31s
Independent scores from Artificial Analysis and DesignArena · updated 10/5/2026. Higher is better; ranks compare against every model we track with that score.
Rates
Gemini 2.5 Flash-Lite pricing
Pricing is based on token usage. Provider-specific caching, batch, regional, and tool charges may affect the final cost.
Input · Standard
$0.10
Per 1M tokens
Cached input · Standard
$0.01
Per 1M tokens
Capabilities
Gemini 2.5 Flash-Lite Tools
Tools available when using Gemini 2.5 Flash-Lite through supported provider APIs.
Function calling
Supported
Structured outputs
Supported
JSON mode
Supported
Reasoning
Supported
Built-in web search
Not supported
Log probabilities
Not supported
Deterministic seed
Supported
Parallel tool calls
Not supported
Prompt caching
Supported
Where to run it
Gemini 2.5 Flash-Lite API providers
5 providers serve Gemini 2.5 Flash-Lite. Prices are per 1M tokens; uptime is the last 24 hours.
| Provider | Input | Output | Cached | Context | Uptime |
|---|---|---|---|---|---|
| $0.10 | $0.40 | $0.01 | 1M | 99.96% | |
| $0.10 | $0.40 | $0.01 | 1M | 99.26% | |
| Google AI Studio | $0.05 | $0.20 | $0.0050 | 1M | 99.99% |
| Google AI Studio | $0.10 | $0.40 | $0.01 | 1M | 99.96% |
| Google AI Studio | $0.18 | $0.72 | $0.02 | 1M | 99.95% |
- Input
- $0.10
- Output
- $0.40
- Cached
- $0.01
- Context
- 1M
- Uptime
- 99.96%
- Input
- $0.10
- Output
- $0.40
- Cached
- $0.01
- Context
- 1M
- Uptime
- 99.26%
- Input
- $0.05
- Output
- $0.20
- Cached
- $0.0050
- Context
- 1M
- Uptime
- 99.99%
- Input
- $0.10
- Output
- $0.40
- Cached
- $0.01
- Context
- 1M
- Uptime
- 99.96%
- Input
- $0.18
- Output
- $0.72
- Cached
- $0.02
- Context
- 1M
- Uptime
- 99.95%
Strengths and limitations
Strengths
- Low input cost at $0.10 per million tokens suits high-volume workloads.
- 1M context supports large documents, repositories and extended conversations.
- Supports text & reasoning and vision workloads in one model.
Limitations
- Generated tokens cost 4× more than input tokens, which matters for verbose responses.
- Large context capacity does not guarantee consistent retrieval across the entire prompt.
- Arena Elo and MMLU-Pro are directional; test accuracy, latency and reliability on your own workload before committing.
Arena Elo, MMLU-Pro and pricing figures are illustrative; validate current vendor terms before purchase.
Same provider
