Google Gemini and Vertex AI
Google DeepMind's Gemini family is the third major frontier LLM alongside OpenAI and Anthropic. Gemini leads on several dimensions: long context (up to 2M tokens), multimodal understanding (text, image, audio, video, code), and deep integration with Google Cloud's data platform via Vertex AI. For GCP-centric enterprises and for workloads where the content is multimodal, Gemini is often the right model choice.
How Thoughtwave integrates Gemini
Our Gemini engagements cover:
- Vertex AI Model Garden as the primary enterprise access layer — Gemini models plus Anthropic Claude (through the Vertex partnership), Llama, Mistral, and Google's open models.
- Generative AI on Vertex with grounding to Vertex AI Search for RAG workloads over the client's proprietary content.
- Gemini 2.0+ models including Flash for cost-sensitive workloads and Pro/Ultra tiers for reasoning-heavy tasks.
- Multimodal workflows where the AI needs to process images, documents, or video alongside text — insurance claims processing, inspection reporting, content-moderation pipelines.
- TPU access for large-scale training or inference workloads where Google's specialized hardware matters.
Our TWSS AI Custom Agents platform supports Gemini as a model choice; selection is per-workload based on quality, cost, and the client's cloud preference.
Authentication and governance
Vertex AI authentication runs under Google Cloud IAM with service-account-based access for workloads and OAuth for user-driven flows. Data-processing terms and regional residency (including EU-hosted options) align to the client's compliance posture. For clients requiring a BAA, Google Cloud Healthcare APIs integrate with Gemini under appropriate commercial terms.
When Gemini wins the evaluation
Empirically, Gemini leads in three categories: long-context workloads where the full document corpus fits in a single prompt (2M tokens is materially bigger than competitors), multimodal tasks combining text and image or video, and GCP-native deployments where BigQuery and Vertex are already the client's data platform. For narrower text-only workloads the competition among Claude, GPT, and Gemini is workload-specific — we evaluate empirically on the client's actual data rather than defaulting.