Google Gemini API
Multimodal AI — text, images, audio, video and code
Freemium
✓ Verified
🇺🇸 United States
Google’s Gemini API provides access to Google DeepMind’s flagship multimodal models. Gemini 2.5 Pro features a 1 million token context window and excels at reasoning, coding, and multimodal tasks including image, audio, and video understanding. The free Gemini Flash tier makes it accessible for prototyping and low-volume apps. Available through Google AI Studio, Vertex AI, and direct API access. Native integration with Google Workspace and Firebase makes it particularly powerful for apps within the Google ecosystem.
API Details
Auth Method
API Key
Pricing Model
Freemium
Free Tier
Yes — Gemini Flash free tier available
Rate Limit
60 RPM (free), higher on paid
Format
REST / JSON
Versioning
Model-based (gemini-2.5-pro, gemini-2.0-flash)
SLA / Uptime
99.9% (paid)
Compliance
SOC 2, ISO 27001, GDPR
Geographic Restrictions
Available in 200+ countries; China and some regions excluded
Last Verified
2026-02-20
Categories
Frequently Asked Questions
Yes Gemini API has a free tier through Google AI Studio with generous limits (15 RPM, 1 million TPM for Gemini 1.5 Flash). The paid tier via Google Cloud (Vertex AI) has no RPM limits and enterprise SLAs. Gemini 1.5 Flash is one of the most cost-effective models at $0.075 per million input tokens.
Gemini is Google's natively multimodal model was trained on text, images, audio, and video simultaneously rather than added as separate capabilities. Gemini 1.5 Pro has a 1 million token context window (2 million in preview), and Gemini 1.5 Flash is the fastest and cheapest option for high-throughput applications.
Yes. Gemini is natively multimodal and can analyse images, PDFs, audio files, and video. Gemini 1.5 Pro can process up to 1 hour of video, 8 hours of audio, or 3,600 images per request. This is significantly more capable than most competing models for multimedia tasks.
Yes. Google provides an OpenAI-compatible endpoint so you can use the official OpenAI Python or Node.js SDK with Gemini models by just changing the base URL and model name. This makes it easy to test Gemini as a drop-in replacement without rewriting your integration code.