Context Window
1.0M tokens
Input Price/1M
$0.30
Output Price/1M
$2.50
Parameters
—
Speed
404 tok/s
Latency (TTFT)
7.3s
Max Output
66K tokens
Gemini 3.5 Flash-Lite results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Coding Index | 49.3 | 100.0 | — |
| SciCode | 41.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 62.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| LMArena Elo | 1460.0 | 2000.0 | Crowdsourced blind pairwise comparisons |
| AA Intelligence Index | 36.5 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| GPQA Diamond | 84.0 | 100.0 | — |
| HLE | 18.0 | 100.0 | — |
Gemini 3.5 Flash-Lite is an AI model developed by Google, classified as a text model. It focuses on text processing and natural language generation. As a proprietary model, it is available via Google's cloud API. With a context window of 1.0M tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Gemini 3.5 Flash-Lite is usage-based, priced at $0.3/1M input tokens and $2.5/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Gemini 3.5 Flash-Lite was evaluated on 7 different benchmarks, covering categories like Coding, Long Context, overall, Reasoning. Results show exceptional performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Gemini 3.5 Flash-Lite specializes in text, offering advanced capabilities for creating and processing text content.
In the 2026 AI model ecosystem, Gemini 3.5 Flash-Lite competes directly with similarly capable models. Key competitors include GPT (OpenAI), Claude (Anthropic), and open source models like Llama (Meta) and Qwen (Alibaba). The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Gemini 3.5 Flash-Lite is an AI model developed by Google. It is a text model.
Gemini 3.5 Flash-Lite costs $0.3/1M input tokens and $2.5/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
In available benchmarks, Gemini 3.5 Flash-Lite scored: AA Coding Index: 49.3/100, SciCode: 41/100, AA-LCR: 62/100. See the full table above for a detailed comparison.
No, Gemini 3.5 Flash-Lite is a proprietary model from Google. It is available via cloud API. For open source alternatives, check our open source model ranking.
Gemini 3.5 Flash-Lite excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations.
Last updated: July 28, 2026 • View methodology →