AI Models. Google Gemini
Multimodal / Google Cloud / BigQuery

Google Gemini

3.5 Flash, 3.1 Pro, Vertex AI, Zero Data Retention

Gemini 3.1 Pro (02/19/2026) and Gemini 3.5 Flash (05/19/2026, Google I/O) are natively multimodal models (text, audio, image, video); Gemini 3.5 Pro announced. Access via Gemini API and Vertex AI; Zero Data Retention options depending on configuration. Model cards publish limitations and evaluation results (MMLU-Pro, LiveBench, Arena-Hard, OSWorld).

Verified: 2026-05-22

Purchase decision (when to choose / when to avoid)

Choose if...

  • You're in the Google ecosystem (GCP/BigQuery/Looker/Vertex) and want consistent governance.
  • You have multimodal use cases (text + images + audio/video) and agentic workflows.
  • You need model cards and compliance materials (AI Act/GPAI).

Avoid if...

  • You don't use GCP and want minimal operational complexity — compare other SaaS options.
  • You have very restrictive region/retention requirements — verify in service settings (ZDR).

Cost in practice (scenarios)

Analytics team in GCP

Usually: Vertex AI + GCP billing.

  • BigQuery/Looker
  • governance and IAM
Multimodal (audio/video/images)

Cost depends on modality and context length; plan limits.

  • material analysis
  • pipelines
Marketing (copy + briefs)

Gemini App/Workspace + optional API for automation.

  • daily work
  • moderate volume
These are estimates/scenarios (not an invoice). Actual cost depends on context length, number of users, limits and retention policies.

Deployment / data / enterprise

Deployment channels

  • Gemini App
  • Gemini API (AI Studio)
  • Vertex AI (Google Cloud)
  • Integrations in Google ecosystem (e.g. Workspace)

Data policy

Training on data
Paid tiers usually don't use data for product improvement (check terms).
Retention
Depends on service and configuration (AI Studio vs Vertex).
Data residency
Regions depend on GCP/Vertex; retention/ZDR settings possible.
Works best when you're already in GCP — governance and billing are unified.

Enterprise readiness

Admin
GCP/Vertex: central billing and IAM.
SSO/SCIM
Via GCP/Workspace (depending on product).
Audit
Via GCP/Workspace (depending on product).
DPA
Depending on GCP/Workspace agreement.
Certifications
Depending on GCP/Workspace (check documentation).
Good choice for companies with data in BigQuery wanting agentic workflows.

Best use cases

  • projects in Google Cloud (BigQuery, Looker, Sheets, Docs, Vertex AI)
  • multimodal scenarios and ML pipelines with governance/retention requirements (ZDR).
  • assistants and automations based on GCP data with model documentation needs (AI Act/GPAI).

Strengths

  • Native multimodality and enterprise maturity via Vertex AI; Zero Data Retention options.
  • Gemini 3.5 Flash — fast, cost-efficient variant; 3.1 Pro — flagship reasoning.
  • Permission management and billing in a single GCP account.

Weaknesses / risks

  • Platform dependency; governance sensitive to region and data policy. PaLM 2 (legacy) in the context of EU data protection regulator investigation.
  • Requires DPIA and legal basis for personal data; Vertex configuration can be complex for smaller teams.

Current models (examples)

  • Gemini 3.5 Flash — 05/19/2026 (Google I/O); Gemini 3.1 Pro — 02/19/2026.
  • Gemini 3.5 Pro — announced; access via Gemini API / Vertex AI.

Alternatives (if this model doesn't fit)

OP
OpenAI
widest tool and integration ecosystem
CL
Claude
excellent long-context and safety
MI
Mistral
EU + self-host/open-weight (depending on model)