Gemini 3.6 Flash
gemini-3.6-flash
Total Context
1M
Max Output
65.5K
Released
N/A
Input$1.5 / M tokens
Output$7.5 / M tokens
Gemini 2.5 Flash-Lite
gemini-2.5-flash-liteGemini 2.5 Flash-Lite is Google’s fastest and most budget-friendly Gemini 2.5 option. Official docs highlight low latency, low cost, multimodal support, thinking budgets, and tool integrations such as grounding and code execution. It is best described for classification, translation, routing, extraction, and high-scale workloads.
Context Window
1M tokens
Maximum Output
65.5K tokens
Release Date
Jun 17, 2025
Modalities
Gemini 2.5 Flash-Lite Pricing
| Input Price | Output Price | Cache Read |
|---|---|---|
| $0.1/M | $0.4/M | $0.01/M |
Gemini 2.5 Flash-Lite API Capabilities
Reasoning
Supported
Tool calling
Supported
Temperature parameter
Supported
Attachments
Supported
Knowledge Base
2025-01-01
Endpoint Protocols
geminiCompletions APIMessages API
Gemini 2.5 Flash-Lite Model Highlights
Gemini 2.5 Flash-Lite prioritizes low latency and efficient multimodal processing for frequent, lightweight tasks at scale.
Low-Latency Processing
The model is optimized for fast execution of lightweight requests, supporting responsive applications and high-frequency processing.
Broad Multimodal Input
It can interpret text, images, video, audio and PDF files while producing text responses for downstream applications.
Large Input Window
Its 1,048,576-token input limit allows lightweight processing to cover long documents and sizeable collections in fewer requests.
Gemini 2.5 Flash-Lite Use Cases
Gemini 2.5 Flash-Lite fits high-volume classification, straightforward extraction and latency-sensitive content processing.
High-Volume Classification
Assign categories, priorities or moderation labels to large streams of text and multimodal content with fast turnaround.
Simple Data Extraction
Extract routine fields and facts from messages, forms, images or PDF files for indexing and downstream automation.
Rapid Document Summaries
Condense lengthy documents and PDFs into short overviews, key points or routing metadata for content pipelines.
How to Use Gemini 2.5 Flash-Lite via the TokenHub API
Replace these path values before running: {model}
curl 'https://us-api.tokenhub.com/v1beta/models/{model}:generateContent' \
-X 'POST' \
-H "Authorization: Bearer $TOKENHUB_API_KEY"Gemini 2.5 Flash-Lite Benchmarks
| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 11.4 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 9.5 |
| Artificial Analysis Math Index | Artificial Analysis math reasoning aggregate | 53.3 |
| Knowledge & Reasoning | ||
| MMLU-Pro | Advanced multi-task knowledge | 75.9% |
| GPQA | Advanced science problem solving | 62.5% |
| HLE | Broad expert-level exam set | 6.4% |
| Coding & Engineering | ||
| LiveCodeBench | Live coding problems | 59.3% |
| SciCode | Scientific coding challenges | 19.3% |
| Terminal-Bench Hard | Hard terminal task execution | 4.5% |
| Math | ||
| MATH-500 | Advanced math problem solving | 96.9% |
| AIME | Competition math problems | 70.3% |
| AIME 2025 | Competition math problems | 53.3% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 49.9% |
| AA-LCR | Long-context reasoning | 51.3% |
| τ²-Bench | Agent workflow tasks | 18.4% |
Metrics sourced from Artificial Analysis
Frequently asked questions about Gemini 2.5 Flash-Lite
Understand what Gemini 2.5 Flash-Lite is, its best uses, distinguishing strengths, practical tradeoffs, and safe TokenHub integration guidance.
What kind of model is Gemini 2.5 Flash-Lite?+
Gemini 2.5 Flash-Lite is Google’s most economical Gemini 2.5 model for simple, high-frequency multimodal processing. It remains a defined model generation, but newer models in the same family may be preferable for new evaluations.
What should teams use Gemini 2.5 Flash-Lite for?+
Best-fit scenarios include large-scale classification and routing, simple structured data extraction, and high-volume translation. Test representative inputs and define measurable acceptance criteria before production.
Where does Gemini 2.5 Flash-Lite have a clear technical advantage?+
Key strengths include cost-efficient scaling, fast response times, and support for varied multimodal inputs. This combination is especially useful for simple structured data extraction.
When should a team choose another model instead of Gemini 2.5 Flash-Lite?+
Consider another model when the workload involves difficult multi-step reasoning, the project can adopt a newer Gemini generation, or the workflow cannot include human review for important decisions. Verify important factual, legal, financial, medical, or operational outputs with qualified human review.
What should be checked before integrating Gemini 2.5 Flash-Lite with TokenHub?+
In TokenHub, select the exact model identifier displayed for Gemini 2.5 Flash-Lite, use the endpoint documented for your account, and authenticate with your TokenHub credentials. Confirm the TokenHub-exposed input types, tools, grounding options, and model lifecycle rather than assuming full Gemini API parity.
Ready to use Gemini 2.5 Flash-Lite?
Use one API key to access Gemini 2.5 Flash-Lite and more AI models through TokenHub.
Media and Discussions
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