Google: Gemini 2.5 Flash Lite
Gemini 2.5 Flash Lite from Google is an ultra-affordable model with a massive 1M token context window and full multimodal support, making it a strong choice for high-volume, cost-sensitive workflows. Its reasoning and coding benchmarks are modest, so it is best suited to lighter tasks such as summarisation, content drafting, and structured data extraction rather than complex reasoning.
Assessment date: March 14, 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
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
Evaluations
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.
