Google AI APIs in 2026: Gemini, Vertex AI, Vision & Everything Else

Google has an AI API for nearly every task — which is both its strength and the reason developers get lost. This guide cuts through it: what each service does, when to reach for it, and what it costs. Read it once and you'll know exactly which Google API to wire up for any feature.

The two platforms

1. Google AI Studio / Gemini API — the fast path: a simple API key and direct access to Gemini.
2. Google Cloud Vertex AI — the enterprise path: managed training, deployment, MLOps, governance.

Use the Gemini API for straightforward inference; move to Vertex AI when you need fine-tuning, model hosting, or enterprise controls.

Gemini API — the flagship

Google Gemini is natively multimodal (text, images, audio, video) with an enormous context window.

• Gemini 3.1 Pro — up to a 2M-token context window; for whole-codebase or whole-corpus reasoning (~$2 / $12 per 1M tokens up to 200K).
• Gemini 3.5 Flash — punches far above its price on coding and agentic tasks (~$1.50 / $9).
• Gemini 3.1 Flash-Lite — the budget option (~$0.25 / $1.50).

from google import genai

client = genai.Client(api_key="YOUR_API_KEY")
resp = client.models.generate_content(
    model="gemini-3.1-pro",
    contents="Analyze this 300-page PDF and list every financial risk."
)
print(resp.text)

Gemini also supports grounding with Google Search for fresh facts and native function calling for tools.

Cloud Vision API — image analysis

Google Cloud AI's Vision API offers label detection, OCR in 100+ languages, face and landmark detection, logo recognition, and safe-search moderation.

from google.cloud import vision
client = vision.ImageAnnotatorClient()
with open("image.jpg", "rb") as f:
    image = vision.Image(content=f.read())
for label in client.label_detection(image=image).label_annotations:
    print(f"{label.description}: {label.score:.2f}")

Pricing: first 1,000 units/month free, then ~$1.50 per 1,000 units for most features.

Tip: for describing or reasoning about images, Gemini's multimodal understanding is often the better tool; use Vision for structured detection (labels, OCR, faces).

Speech-to-Text — Chirp

Google's Chirp models cover 125+ languages with streaming, diarization, and automatic punctuation. See our speech-to-text comparison for how it stacks up against Deepgram and AssemblyAI.

Translation API

Neural machine translation for 130+ languages, with glossaries and custom models. First 500K characters/month free, then ~$20 per million characters.

from google.cloud import translate_v2 as translate
client = translate.Client()
print(client.translate("Hello, how are you?", target_language="es")["translatedText"])

For translation-specialist quality, also compare DeepL.

Natural Language API

Document- and sentence-level sentiment, entity recognition, and content classification into 700+ categories. First 5,000 units/month free.

Dialogflow — conversational interfaces

Dialogflow builds chatbots and voice assistants with a visual flow designer and strong NLU. See our chatbot guide for where it fits versus LLM-first approaches.

Vertex AI — the enterprise platform

Vertex AI unifies everything: managed training and deployment, MLOps, AutoML, a Model Garden of pre-trained models, and evaluation tools. Reach for it when you need customization, governance, or fine-tuning — not for simple inference.

Which Google AI API should you use?

Why developers pick Google AI

• Generous free tiers on most services
• Massive context windows (up to 2M tokens)
• Strong price/performance, especially Gemini Flash
• One $300 free-trial credit to evaluate the whole platform

Browse all Google AI services and alternatives in our AI API directory.