Gemini Enterprise Pricing
For organisations running Gemini at scale, Google Cloud offers enterprise pricing through Vertex AI with volume discounts, committed use agreements, provisioned throughput, and full compliance coverage. This guide covers everything you need to plan your enterprise AI budget.
Enterprise Gemini Access Through Vertex AI
Google does not offer a standalone "Gemini Enterprise" product. Instead, enterprise access to Gemini is delivered through Vertex AI, Google Cloud's AI platform. This means your Gemini usage is managed alongside your other Google Cloud services, with unified billing, IAM, and compliance controls.
The base per-token pricing on Vertex AI is the same as Google AI Studio. Enterprise savings come from three mechanisms: committed use discounts (lower per-token rates in exchange for minimum spend commitments), provisioned throughput (reserved capacity at a fixed hourly rate), and negotiated custom pricing for very large deployments.
To access enterprise pricing, you need an active Google Cloud account with billing enabled. New accounts receive $300 in free trial credits. For committed use discounts, you will work directly with a Google Cloud sales representative who can provide custom quotes based on your projected volume.
| Model | Input / 1M Tokens | Output / 1M Tokens | 1-Year CUD Est. | 3-Year CUD Est. |
|---|---|---|---|---|
| Gemini 2.5 Pro | $1.25 | $10.00 | ~$1.00 | ~$0.75 |
| Gemini 2.5 Flash | $0.15 | $0.60 | ~$0.12 | ~$0.09 |
| Gemini 2.0 Flash | $0.10 | $0.40 | ~$0.08 | ~$0.06 |
CUD estimates are approximate. Actual discounts vary based on commitment level and are negotiated with Google Cloud sales.
Committed Use Discounts (CUDs)
Committed use discounts are the primary mechanism for reducing enterprise Gemini costs. You agree to a minimum monthly spend on Vertex AI over a fixed term, and Google provides reduced per-unit pricing in return.
CUDs come in two standard terms:
1-Year Commitment
~20% savings
- Lower barrier to entry
- Good for growing workloads where you have reasonable forecasts
- Minimum spend applies monthly, not as a lump sum
- Can be renewed or upgraded to a 3-year term at expiration
3-Year Commitment
~40% savings
- Maximum discount tier
- Best for stable, high-volume production workloads
- Requires confidence in long-term Gemini usage
- May include additional support and priority access benefits
Important: CUD commitments are binding. If your actual usage falls below the committed minimum, you still pay the minimum amount. Forecast your usage carefully before signing a multi-year agreement. Google Cloud sales can help you model different scenarios.
Provisioned Throughput
Standard Vertex AI usage is shared capacity: your requests compete with other users for inference resources, which means latency and availability can fluctuate during peak periods. Provisioned throughput eliminates this variability by reserving dedicated capacity for your workload.
With provisioned throughput, you pay a fixed hourly rate for a guaranteed number of tokens per second. This capacity is exclusively yours, so you get consistent latency regardless of overall platform load. The trade-off is cost: you pay for the reserved capacity whether you use it or not.
Provisioned throughput is priced per-model and varies based on the throughput tier you reserve. Contact Google Cloud sales for specific hourly rates. As a general guideline, provisioned throughput becomes cost-effective when you are consistently using more than 70% of your reserved capacity and when latency consistency is a hard requirement for your application.
When Provisioned Throughput Makes Sense
Customer-facing chatbots
Users expect fast, consistent responses. Variable latency hurts user experience and conversion rates.
Real-time data pipelines
Processing streams of data where delays compound. Consistent throughput prevents bottlenecks.
High-frequency trading tools
Any application where milliseconds of latency variance directly impacts business outcomes.
SLA-bound applications
When you have contractual latency commitments to your own customers that you must guarantee.
Data Residency and Compliance
Enterprise AI deployments in regulated industries require strict compliance controls. Vertex AI provides these through Google Cloud's compliance infrastructure.
| Certification | Coverage | Relevance |
|---|---|---|
| SOC 2 Type II | Vertex AI included | Required by most enterprise procurement teams |
| SOC 3 | Vertex AI included | Public-facing summary of SOC 2 controls |
| ISO 27001 | Google Cloud platform | Information security management standard |
| ISO 27017 | Google Cloud platform | Cloud-specific security controls |
| ISO 27018 | Google Cloud platform | Protection of personal data in the cloud |
| HIPAA | Vertex AI via BAA | Healthcare data protection (US) |
| FedRAMP High | Google Cloud (select regions) | US federal government workloads |
| GDPR | Google Cloud DPA | EU data protection regulation |
Data residency is configurable at the Google Cloud project level. You choose which regions your data is processed and stored in, ensuring compliance with local data sovereignty laws. For Vertex AI specifically, you can restrict Gemini inference to run only in designated regions (for example, keeping all processing within the EU or within the United States).
VPC Service Controls add another layer by creating a security perimeter around your Vertex AI resources. Combined with customer-managed encryption keys (CMEK), this gives you a level of control over your data that is simply not possible on Google AI Studio or most other AI API platforms.
Enterprise Comparison: Gemini vs Claude vs OpenAI
All three major AI providers offer enterprise tiers through cloud platform integrations. Here is how they compare for enterprise buyers.
| Feature | Gemini (Vertex AI) | Claude (Bedrock/Direct) | OpenAI (Azure) |
|---|---|---|---|
| Cloud Platform | Google Cloud | AWS / Direct API | Microsoft Azure |
| Top Model (Input) | $1.25/MTok (2.5 Pro) | $3.00/MTok (Opus) | $2.50/MTok (GPT-4o) |
| Budget Model (Input) | $0.10/MTok (2.0 Flash) | $0.25/MTok (Haiku 3.5) | $0.15/MTok (4o mini) |
| Context Window | 1M tokens | 200K tokens | 128K tokens |
| Committed Use Discounts | 1-year, 3-year CUDs | AWS Savings Plans | Azure Reservations |
| Provisioned Throughput | Yes | Yes (Bedrock) | Yes (Azure PTU) |
| Data Residency | Regional control | Regional (AWS) | Regional (Azure) |
| HIPAA | Yes (BAA) | Yes (via AWS BAA) | Yes (via Azure BAA) |
| SOC 2 | Yes | Yes | Yes |
| Fine-tuning | Yes (Vertex AI) | Limited | Yes (Azure OpenAI) |
| SLA | 99.9% | 99.9% (Bedrock) | 99.9% (Azure) |
The choice between providers often comes down to existing cloud infrastructure. If your organisation is already on Google Cloud, Vertex AI provides the tightest integration. AWS shops may prefer Claude on Bedrock. Azure environments benefit from Azure OpenAI Service. All three offer comparable enterprise controls, and the base model pricing is competitive across the board.
How to Get Enterprise Pricing
Getting started with enterprise Gemini pricing involves a few steps. Here is the typical process.
Set up a Google Cloud account
If you do not already have one, create a Google Cloud account and enable billing. New accounts receive $300 in free credits to test Vertex AI capabilities.
Evaluate with on-demand pricing
Use Vertex AI with standard pay-as-you-go pricing to validate your use case, measure token consumption, and establish baseline costs. This data is essential for negotiating committed use discounts.
Contact Google Cloud sales
Reach out through the Google Cloud sales contact form or your existing Google Cloud account manager. Share your projected monthly spend, preferred commitment term, and any compliance requirements.
Negotiate your agreement
Google Cloud sales will provide a custom quote based on your volume, commitment term, and feature requirements. This may include CUDs, provisioned throughput, and additional support tiers.
Activate and monitor
Once the agreement is signed, discounted rates apply automatically to your Vertex AI usage. Monitor spending through Google Cloud's billing dashboard and cost management tools.
Frequently Asked Questions
How do I get enterprise pricing for Gemini?
Enterprise pricing is available through Google Cloud's Vertex AI platform. Start by setting up a Google Cloud account, evaluate your workload on standard pay-as-you-go pricing, then contact Google Cloud sales to negotiate committed use discounts. Sales can be reached through the Google Cloud website or through your existing account manager.
What volume discounts are available for Gemini?
Google Cloud offers committed use discounts (CUDs) for Vertex AI in two standard terms. A 1-year commitment typically provides around 20% savings on per-token pricing, while a 3-year commitment can save approximately 40%. The exact discount depends on your total committed spend and is negotiated directly with the sales team. Very large deployments may qualify for additional custom pricing.
Does Gemini support HIPAA compliance?
Yes, through Vertex AI on Google Cloud. Vertex AI is covered by Google Cloud's HIPAA Business Associate Agreement (BAA), which means you can process protected health information (PHI) through Gemini models when running on Vertex AI. This is not available through Google AI Studio. You will need to sign Google Cloud's BAA and configure appropriate access controls and data handling procedures.
How does Gemini enterprise pricing compare to OpenAI and Claude?
All three providers offer enterprise tiers through major cloud platforms. Gemini on Vertex AI integrates with Google Cloud, Claude on Bedrock integrates with AWS, and OpenAI on Azure integrates with Microsoft's cloud. Base token prices are competitive across all three. The main differentiators are context window (Gemini leads with 1M tokens), existing cloud provider relationships, and specific model capabilities. Most enterprises choose based on their existing cloud infrastructure rather than per-token pricing differences.
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