Last refreshed 2026-11-13. Next refresh: weekly.
Why use Gemini 4 Hydrogen on GCP Vertex AI?
GCP Vertex AI offers Gemini 4 Hydrogen with pay-as-you-go pricing at $1.50/1M input tokens. Vertex AI is Google Cloud's managed AI platform, offering access to Gemini models and hundreds of partner models alongside tools for fine-tuning, grounding, vector search, and end-to-end MLOps pipelines.
Compare Gemini 4 Hydrogen across 4 providers to find the best fit for your use caseSetup recipe
Python + curlpip install google-cloud-aiplatformexport GOOGLE_CLOUD_PROJECT=...import os
import vertexai
from vertexai.generative_models import GenerativeModel
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")gemini-4-hydrogenRequest example
import os
import vertexai
from vertexai.generative_models import GenerativeModel
# Reads GOOGLE_CLOUD_PROJECT from env; authenticates via Application Default Credentials
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
model = GenerativeModel("gemini-4-hydrogen")
response = model.generate_content("Hello")
print(response.text)Gotchas
- For Google-published models use the model name directly, e.g. "gemini-2.0-flash-001". For third-party publishers (Anthropic, Meta, etc.) use the full publisher path, e.g. "publishers/anthropic/models/claude-3-5-sonnet-v2@20241022".
- The examples expect GOOGLE_CLOUD_PROJECT; rename it only if your application config maps the new variable.
Compare Gemini 4 Hydrogen Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Google AI Studio | $1.50 | $7.50 |
| GCP Vertex AI | $1.50 | $7.50 |
| OpenRouter | $1.50 | $7.50 |
| Vercel AI Gateway | $1.50 | $7.50 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $1.50 |
| Output tokens | $7.50 |
Capabilities
About Gemini 4 Hydrogen
Gemini 4 Hydrogen is Google DeepMind's fast, lower-cost Gemini 4 model, released generally available on November 12, 2026 in the Gemini API, Google AI Studio and Vertex AI (Gemini Enterprise Agent Platform). Google positions it for everyday coding, agentic workflows and multimodal work, alongside Gemini 4 Carbon for the hardest problems; its model card says it is adapted from Gemini 4 Carbon. It takes text, image, video, audio and PDF input and returns text, with a unified 1,048,576-token context window and long decode up to 1,048,576 output tokens (65,536 by default).