Ship a Full-Stack App with One Prompt

Copy this prompt into your AI coding agent, or open it in one below.

Give this to your AI Create a to-do list app using Puter.js

Coding manually? see the guide

Google: Gemini 2.5 Flash-Lite Preview 06-17

This model is no longer available.

Add AI to your application with Puter.js.

Explore Other Models

Model Card

Gemini 2.5 Flash-Lite Preview 06-17 is the June 17, 2025 preview snapshot of Gemini 2.5 Flash-Lite, the fastest and lowest-priced model in Google's Gemini 2.5 family.

It accepts text, image, audio, and video input, has a 1M token context window, and supports tool calling. Thinking is off by default and can be enabled with a thinking budget for harder tasks. Google reported lower latency than Gemini 2.0 Flash and 2.0 Flash-Lite, and higher quality than 2.0 Flash-Lite on coding, math, science, reasoning, and multimodal benchmarks. Artificial Analysis measured it at about 5x cheaper and 1.7x faster than Gemini 2.5 Flash, with lower intelligence.

It fits high-volume, latency-sensitive work such as translation and classification. The stable gemini-2.5-flash-lite superseded this preview at general availability on July 22, 2025, so use this ID only if you need this exact snapshot.

Context Window 1M

tokens

Max Output 66K

tokens

Input Cost $0.08

per million tokens

Output Cost $0.3

per million tokens

Input text, image, audio, video

modalities

Tool Use Yes

 

Release Date Jun 17, 2025

 

Code Example

Add AI to your app with the Puter.js AI API, no API keys or setup required.

// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms").then(response => {
    document.body.innerHTML = response.message.content;
});
<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms").then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

More AI Models From Google

Find other Google models →

Chat

Gemini 4 Argon

Gemini 4 Argon is Google's flagship Gemini 4 model, announced by Google DeepMind on September 30, 2026. It is aimed at long, multi-step software engineering, legal and finance work, and defensive cybersecurity. Google reports 77.9% on DeepSWE v1.1 (Claude Opus 5.5 74.2%, GPT-6 Astra 74.1%) and 19.6% on Harvey's Legal Agent Benchmark. It trails Opus 5.5 on Terminal-bench 4.0 (57.4% vs 66.4%) and GPT-6 Astra on FrontierSWE v2 (55.0% vs 65.5%). Vals.ai places it first on the Vals Index at 68.9%. Introductory pricing is $2 per million input tokens and $10 per million output tokens, rising to $4 and $20 later. It suits teams running coding agents or document-heavy professional workflows.

Image

Gemini Nano Banana 2.1

Gemini Nano Banana 2.1 is Google's image generation and conversational editing model, released in October 2026 as an update to Nano Banana 2 (Gemini 3.1 Flash Image). It keeps Flash-tier speed and cost while improving visual quality, prompt adherence, text rendering, and multi-turn character consistency. It accepts text, image, video, and PDF input and returns images and text. Output is available at 1K, 2K, and 4K, with fixes for tiling artifacts on wide aspect ratios such as 1:8 and 8:1 at 2K and 4K. It can combine up to 14 reference images, and supports search grounding and configurable thinking levels. A 1K image costs $0.0336. Choose it for infographics, text-heavy graphics, and multi-step editing where the same characters must stay consistent across turns.

Chat

Gemini 3.8 Flash

Gemini 3.8 Flash is Google's workhorse Flash-tier model, released September 2, 2026, three weeks after Gemini 3.7 Flash. It's built for long-horizon software engineering, agentic workflows, and multi-step reasoning in professional domains. Google reports it outperforms 3.7 Flash and other frontier models on DeepSWE v1.1 for autonomous engineering tasks, on Vals Finance Agent V2, and on Harvey's Legal Agent Benchmark. It scores 54.9% on HLE-Verified, and completes more than three times as many tasks as 3.7 Flash in Google's long-running, document-heavy workflow evaluations. It accepts text, image, video, audio, and PDF input with a 1M token context window and 64K token output limit, supports function calling and iterative tool use, and has a March 2026 knowledge cutoff. Priced at $0.75 per million input tokens and $3.75 per million output tokens through 2026, it targets teams running coding agents or document-heavy enterprise workflows.

Frequently Asked Questions

How do I use Gemini 2.5 Flash-Lite Preview 06-17?

Gemini 2.5 Flash-Lite Preview 06-17 is no longer available through Puter.js. Explore other AI models for alternatives.

What is the pricing for Gemini 2.5 Flash-Lite Preview 06-17?
Gemini 2.5 Flash-Lite Preview 06-17 costs $0.08 per 1M input tokens and $0.3 per 1M output tokens.
Price per 1M tokens
Input$0.08
Output$0.3
Who created Gemini 2.5 Flash-Lite Preview 06-17?

Gemini 2.5 Flash-Lite Preview 06-17 was created by Google and released on Jun 17, 2025.

What is the context window of Gemini 2.5 Flash-Lite Preview 06-17?

Gemini 2.5 Flash-Lite Preview 06-17 supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,097 pages of text.

What is the max output length of Gemini 2.5 Flash-Lite Preview 06-17?

Gemini 2.5 Flash-Lite Preview 06-17 can generate up to 66K tokens in a single response.

What types of input can Gemini 2.5 Flash-Lite Preview 06-17 process?

Gemini 2.5 Flash-Lite Preview 06-17 accepts the following input types: text, image, audio, video. It produces: text.

Does Gemini 2.5 Flash-Lite Preview 06-17 support tool use (function calling)?

Yes, Gemini 2.5 Flash-Lite Preview 06-17 supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Gemini 2.5 Flash-Lite Preview 06-17 API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Get started with Puter.js

Add AI to your application without worrying about API keys or setup.

Explore Models View Tutorials