Google: Gemini 3.7 Flash
Try Gemini 3.7 Flash for free in your browser, and add it to your app for free with Puter.js AI API.
Try it free Add to your app// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "google/gemini-3.7-flash"
}).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", {
model: "google/gemini-3.7-flash"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
Gemini 3.7 Flash is Google's workhorse Flash-tier model, released August 13, 2026, three weeks after Gemini 3.6 Flash. It's built for coding and agentic workflows, targeting software engineering, web development, and knowledge-dense domains like finance and law.
Google reports gains over Gemini 3.6 Flash on several benchmarks. DeepSWE v1.1 rose from 49.0% to 65.3%, FrontierCode 1.1 from 34.4% to 43.6%, and AutomationBench from 17.0% to 30.4%. On FrontierCode 1.1 it scores above Claude Sonnet 5 (42.7%) and GPT-5.6 Terra (41.3%), though GPT-5.6 Terra edges it out on Terminal-bench 2.1 (87.4% vs 85.8%).
It accepts text, image, video, audio, and PDF input with a 1M token context window and 64K token output limit. It supports function calling, search as a tool, and computer use, and has a March 2026 knowledge cutoff. It's priced at roughly half of Gemini 3.6 Flash's rate, fitting teams running coding agents or high-volume document processing.
Context Window 1M
tokens
Max Output 66K
tokens
Input Cost $0.75
per million tokens
Output Cost $3.75
per million tokens
Input text, image, video, audio, pdf
modalities
Tool Use Yes
Knowledge Cutoff Mar 2026
Release Date Aug 13, 2026
Try Gemini 3.7 Flash for free
Try Gemini 3.7 Flash instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Gemini 3.7 Flash performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 94.5% |
| Humanity's Last Exam Cross-domain reasoning | 47.9% |
| SciCode Scientific programming | 57.2% |
| LCR Long-context reasoning | 81.7% |
Scores sourced from Artificial Analysis.
Find other Google models →
Gemini 4 Carbon
Gemini 4 Carbon is Google DeepMind's top model in the Gemini 4 family, announced on October 28, 2026 as a step above Gemini 4 Argon. Google built it for long, multi-step software engineering and defensive cybersecurity, such as finding, validating, and patching vulnerabilities. Google reports 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench. It scores 59 on the Artificial Analysis Intelligence Index v5.0, which Google says places it first on that index. It accepts text, image, audio, video, and file input with a 1M-token context window. Google listed launch pricing of $2 per million input tokens and $10 per million output tokens, rising to $4 and $20 later, with cached input 95% cheaper. On Puter it currently costs $1.60 per million input tokens and $8 per million output tokens. It suits coding agents, security tooling, and long-document analysis.
ChatGemini 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.
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.
Frequently Asked Questions
You can access Gemini 3.7 Flash by Google through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Gemini 3.7 Flash is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.
Gemini 3.7 Flash is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price per 1M tokens | |
|---|---|
| Input | $0.75 |
| Output | $3.75 |
Gemini 3.7 Flash was created by Google and released on Aug 13, 2026.
Gemini 3.7 Flash supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,097 pages of text.
Gemini 3.7 Flash can generate up to 66K tokens in a single response.
Gemini 3.7 Flash has a knowledge cutoff date of Mar 2026. This means the model was trained on data available up to that date.
Gemini 3.7 Flash accepts the following input types: text, image, video, audio, pdf. It produces: text.
Yes, Gemini 3.7 Flash supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Gemini 3.7 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.
Add Gemini 3.7 Flash to your app for free
Developers can integrate Gemini 3.7 Flash for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.