Google: Gemini 2.5 Flash Lite
Google's Gemini 2.5 Flash Lite is an exceptionally affordable multimodal model supporting text, image, audio, and video inputs with a massive 1M token context window, making it a strong choice for high-volume, cost-sensitive content tasks despite modest benchmark scores.
Assessment date: April 4, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
Performance Profile
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 across common benchmarks compared to earlier Flash models. By default, "thinking" (i.e. multi-pass reasoning) is disabled to prioritize speed, but developers can enable it via the Reasoning API parameter to selectively trade off cost for intelligence.
Capabilities
Architecture
| Modality | Text + Image + File + Audio + Video → Text |
| Tokenizer | Gemini |
Performance Indices
Source: Artificial Analysis
Benchmark Scores
Intelligence
Technical
Content
Benchmark data from Artificial Analysis and Hugging Face
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.10 | $0.000100 |
| Output | $0.40 | $0.000400 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
