Last refreshed 2026-06-15. Next refresh: weekly.
Why use Gemini 2.5 Pro on GCP Vertex AI?
GCP Vertex AI offers Gemini 2.5 Pro with pay-as-you-go pricing at $1.25/1M 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 2.5 Pro across 4 providers to find the best fit for your use caseInput / 1M
$1.25
Output / 1M
$10.00
Cache
read $0.125
Batch
-50% · in $0.625 / out $5.00
Setup recipe
Python + curlInstall
pip install google-cloud-aiplatformAuth
export GOOGLE_CLOUD_PROJECT=...Call
import os
import vertexai
from vertexai.generative_models import GenerativeModel
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")Model ID
gemini-2.5-proRequest 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-2.5-pro")
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 2.5 Pro Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Google AI Studio | $1.25 | $10.00 |
| GCP Vertex AI | $1.25 | $10.00 |
| OpenRouter | $1.25 | $10.00 |
| Vercel AI Gateway | $1.25 | $10.00 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $1.25 |
| Output tokens | $10.00 |
Capabilities
VisionMultimodalReasoningJSON / Tool useStructured OutputsCode ExecutionPrompt CachingBatch API
About Gemini 2.5 Pro
Google DeepMind's most capable Gemini 2.5 model with native thinking/reasoning support. Features a 1M-token context window, multimodal inputs (text, image, audio, video), function calling, and strong performance across coding, mathematics, and scientific reasoning tasks.
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Model Specs
Released2025-06-17
Context1m
ArchitectureDecoder Only
Knowledge cutoff2025-01