Vertex AI Pricing Explained
Vertex AI is Google Cloud's managed machine learning platform, and it is the enterprise gateway to Gemini models. This guide breaks down exactly what you pay for, how it compares to Google AI Studio, and when the added cost makes sense for your workload.
What Is Vertex AI and How Does It Relate to Gemini?
Vertex AI is Google Cloud's unified AI development platform. It provides tools for training, deploying, and managing machine learning models at scale. When Google released the Gemini family of models, they made them available through two channels: Google AI Studio (a lightweight, developer-friendly interface) and Vertex AI (the full enterprise platform within Google Cloud).
Think of Google AI Studio as the front door for individual developers and small teams who want quick API access. Vertex AI is the enterprise entrance, offering the same Gemini models wrapped in Google Cloud's security, compliance, and infrastructure tooling.
Both platforms give you access to Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 2.0 Flash, and other models. The core per-token pricing is identical. The difference lies in the surrounding services: data residency controls, VPC Service Controls, customer-managed encryption keys (CMEK), provisioned throughput, fine-tuning infrastructure, and SLA-backed uptime guarantees.
Key takeaway: You do not pay more for Gemini tokens on Vertex AI. You pay for the additional Google Cloud features, infrastructure, and enterprise capabilities that surround the models.
Vertex AI vs Google AI Studio: Pricing Comparison
The table below shows the per-token pricing for each Gemini model on both platforms. As you can see, the base model prices are the same. The differences emerge in rate limits, free tier access, and additional service costs.
| Model | Input / 1M | Output / 1M | AI Studio Free Tier | Vertex AI Free Tier |
|---|---|---|---|---|
| Gemini 2.5 Pro | $1.25 | $10.00 | 5 RPM, 25 RPD | None |
| Gemini 2.5 Flash | $0.15 | $0.60 | 15 RPM, 1,500 RPD | None |
| Gemini 2.0 Flash | $0.10 | $0.40 | 15 RPM, 1,500 RPD | None |
All models support 1M token context windows. Prices are the same on both platforms. Vertex AI does not offer a free tier for Gemini, but new Google Cloud accounts receive $300 in trial credits.
Pay-as-You-Go Model
Vertex AI uses a straightforward pay-as-you-go billing model. You are charged for the exact number of input and output tokens processed, with no minimum commitments or monthly fees for basic API access. Billing is tied to your Google Cloud project and appears on your standard Google Cloud invoice.
This makes it easy to start small and scale up. A team running 10,000 requests per day with Gemini 2.5 Flash (averaging 1,000 input tokens and 500 output tokens per request) would pay approximately:
Input: 10,000 x 1,000 tokens = 10M tokens x $0.15/1M = $1.50/day
Output: 10,000 x 500 tokens = 5M tokens x $0.60/1M = $3.00/day
Total: $4.50/day or roughly $135/month
Committed Use Discounts
For predictable, high-volume workloads, Google Cloud offers Committed Use Discounts (CUDs). These work similarly to reserved instances in other cloud providers. You commit to a minimum monthly spend in exchange for lower per-unit pricing.
| Commitment Term | Estimated Discount | Best For |
|---|---|---|
| No commitment | 0% | Variable workloads, experimentation |
| 1-year CUD | ~20% off | Steady production workloads |
| 3-year CUD | ~40% off | Large-scale, long-term deployments |
Exact discount percentages vary. Contact Google Cloud sales for a custom quote based on your projected usage.
Additional Vertex AI Costs
Beyond basic token-based pricing, Vertex AI offers several premium features that carry their own costs. Understanding these is important for accurate budgeting.
Grounding with Google Search
Per-requestConnect Gemini responses to real-time Google Search results. Charged per grounding request on top of standard token costs. Pricing varies by volume but typically adds $5 per 1,000 grounded requests.
Model Fine-tuning
Compute hoursCustomize Gemini models on your own data using supervised fine-tuning. You pay for training compute (charged per training hour) plus hosting for the tuned model. Training a Gemini Flash model can start at a few dollars per training run for small datasets.
Model Evaluation
Per-evaluationVertex AI provides automated evaluation pipelines to benchmark model quality. Each evaluation job consumes inference tokens and may incur additional orchestration charges depending on the evaluation framework used.
Provisioned Throughput
Hourly rateReserve dedicated capacity for consistent, low-latency inference. You pay a fixed hourly rate for your reserved throughput tier, regardless of actual usage. This guarantees availability during peak demand but costs significantly more than on-demand pricing.
Data Storage and Logging
GCS ratesVertex AI stores training data, model artifacts, and request logs in Google Cloud Storage and BigQuery. Standard GCS and BigQuery storage fees apply. Logging can be disabled to reduce costs if not needed for compliance.
When to Use Vertex AI vs Google AI Studio
The choice between platforms depends on your stage, scale, and compliance requirements. Here is a practical breakdown.
Use Google AI Studio When...
- +You are prototyping or building a proof of concept
- +Your team is small and does not need enterprise compliance
- +You want a free tier with no billing setup
- +You need quick API key access without a Google Cloud project
- +Your traffic is low to moderate and bursty
Use Vertex AI When...
- +You are running production workloads with SLA requirements
- +You need data residency, CMEK, or VPC-SC controls
- +You want committed use discounts for predictable costs
- +You need fine-tuning, evaluation, or grounding features
- +Your organisation already uses Google Cloud for other services
Enterprise Features on Vertex AI
Vertex AI is the only way to access Gemini with full enterprise-grade controls. These features are not available on Google AI Studio.
| Feature | Description |
|---|---|
| VPC Service Controls | Restrict API access to specific VPC networks. Prevents data exfiltration and ensures all traffic stays within your cloud perimeter. |
| Customer-Managed Encryption (CMEK) | Encrypt data at rest with your own keys stored in Cloud KMS. Required by many regulated industries. |
| Data Residency | Control where your data is processed and stored. Choose specific Google Cloud regions for compliance with GDPR, data sovereignty laws, and internal policies. |
| SLA Guarantee | Vertex AI offers a 99.9% uptime SLA for production endpoints. Google AI Studio does not provide any SLA. |
| SOC 2 / HIPAA / ISO 27001 | Vertex AI is covered by Google Cloud's compliance certifications. Critical for healthcare, finance, and government workloads. |
| IAM Integration | Fine-grained access controls using Google Cloud IAM. Manage who can call which models, view logs, or modify configurations. |
| Audit Logging | Every API call is logged in Cloud Audit Logs. Essential for compliance audits and security monitoring. |
If your organisation handles sensitive data or operates in a regulated industry, Vertex AI is the only viable option for running Gemini in production. The cost premium over AI Studio is primarily in these infrastructure and compliance features, not in the model pricing itself.
Frequently Asked Questions
Is Vertex AI more expensive than Google AI Studio?
The per-token prices for Gemini models are identical on both platforms. However, Vertex AI can incur additional costs for features like Grounding with Google Search, fine-tuning, model evaluation, and Google Cloud infrastructure (storage, networking, logging). Google AI Studio is free to start and does not require a billing account for usage within its free tier limits.
Do I need a Google Cloud account to use Vertex AI?
Yes. Vertex AI is a Google Cloud service that requires an active Google Cloud project with billing enabled. New accounts receive $300 in free credits valid for 90 days, which can be applied to Vertex AI usage including Gemini API calls, fine-tuning, and evaluation jobs.
What are committed use discounts on Vertex AI?
Committed use discounts (CUDs) are agreements to maintain a minimum level of spending on Google Cloud over a 1-year or 3-year term. In return, you receive discounted rates of approximately 20% (1-year) to 40% (3-year) off standard pricing. These discounts apply to Vertex AI inference costs and can significantly reduce the total cost of high-volume production workloads.
Can I use the Gemini free tier on Vertex AI?
Vertex AI does not offer the same free tier as Google AI Studio. On AI Studio, you can use Gemini 2.0 Flash for free at 15 requests per minute and 1,500 requests per day with no billing account required. On Vertex AI, all usage is billed from the first token. However, the $300 in free Google Cloud trial credits can effectively serve as a free tier for new users exploring the platform.
Ready to Get Started?
Try the Gemini API for free on Google AI Studio, or set up Vertex AI for production workloads with enterprise controls.