Google: Gemini 2.0 Flash
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Model Card
Gemini 2.0 Flash is Google's fast multimodal model with native tool use, 1M token context window, and support for text, images, video, and audio input. It's optimized for agentic workflows with low latency and cost-efficient inference.
Context Window 131K
tokens
Max Output 8K
tokens
Input Cost $0.1
per million tokens
Output Cost $0.4
per million tokens
Input text, image, audio, video, pdf
modalities
Tool Use Yes
Knowledge Cutoff Jun 2024
Release Date Dec 11, 2024
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>
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ImageGemini 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.
ChatGemini 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
Gemini 2.0 Flash is no longer available through Puter.js. Explore other AI models for alternatives.
| Price per 1M tokens | |
|---|---|
| Input | $0.1 |
| Output | $0.4 |
Gemini 2.0 Flash was created by Google and released on Dec 11, 2024.
Gemini 2.0 Flash supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Gemini 2.0 Flash can generate up to 8K tokens in a single response.
Gemini 2.0 Flash has a knowledge cutoff date of Jun 2024. This means the model was trained on data available up to that date.
Gemini 2.0 Flash accepts the following input types: text, image, audio, video, pdf. It produces: text.
Yes, Gemini 2.0 Flash supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Gemini 2.0 Flash scores 8.9 on the Artificial Analysis Intelligence Index, outperforming 35% of tracked models. On math, it scores 21.7 (outperforms 23% of models).
Yes — the Gemini 2.0 Flash 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.
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