Gemini 2.5 Flash Lite
Google · released Jul 22, 2025
Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...
Specification
- Context window
- 1.05M
- Max output
- 66K
- Knowledge cutoff
- Jan 31, 2025
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 2
- Moderated
- No
- Uptime
- 99.9%
Intelligence
6.7
22th percentile
Coding
—
Coding Index
Agentic
—
Agentic Index
Output speed
108 t/s
Median across providers
Latency
352ms
Time to first token
Cost per task
$0.04
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- MMLU-Pro72.4%
- GPQA Diamond47.4%
- LiveCodeBench40.0%
- AIME 202535.3%
- AA-LCR (long context)32.0%
- IFBench31.5%
- τ²-bench (Telecom)19.0%
- SciCode17.7%
- Humanity's Last Exam3.7%
- Terminal-Bench Hard2.3%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| MMLU-Pro | 72.4% |
| GPQA Diamond | 47.4% |
| LiveCodeBench | 40.0% |
| AIME 2025 | 35.3% |
| AA-LCR (long context) | 32.0% |
| IFBench | 31.5% |
| τ²-bench (Telecom) | 19.0% |
| SciCode | 17.7% |
| Humanity's Last Exam | 3.7% |
| Terminal-Bench Hard | 2.3% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Mistral Large 2407Mistral AI7.0
- 6.9
- GLM 4.5VZ.ai6.8
- GPT-4OpenAI6.8
- Gemini 2.5 Flash LiteGoogle6.7
- GPT-4o-miniOpenAI6.7
- GPT-4o-mini (2024-07-18)OpenAI6.7
- Granite 4.1 8BIBM Granite6.4
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Mistral Large 2407 | 7.0 |
| Qwen2.5 Coder 32B Instruct | 6.9 |
| GLM 4.5V | 6.8 |
| GPT-4 | 6.8 |
| Gemini 2.5 Flash Lite | 6.7 |
| GPT-4o-mini | 6.7 |
| GPT-4o-mini (2024-07-18) | 6.7 |
| Granite 4.1 8B | 6.4 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.1
- Output / 1M tokens
- $0.4
- Cached input / 1M
- $0.01
- Blended 3:1
- $0.175
One task, estimated
$0.04
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.