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Google Gemini vs Amazon Bedrock

A feature-by-feature comparison of Google Gemini and Amazon Bedrock across 7 capability categories.

First tool

Try Google Gemini (opens in a new tab)

Second tool

Try Amazon Bedrock (opens in a new tab)

Modalities — Google Gemini Wins

Modalities: Google Gemini compared with Amazon Bedrock
Feature	Google Gemini	Amazon Bedrock
Text Input	Yes. Core feature	Yes, requires plus plan. InvokeModel and Converse APIs accept text prompts across hosted FMs.
Image Upload / Vision	Yes	Partial. Multimodal models (e.g. Claude on Bedrock) accept images via the Converse API.
Image Generation	Yes	Partial. Titan Image and third-party image models are in the model catalog. Not a consumer DALL·E-style chat.
Voice Mode	Yes	Unknown. Speech models exist on Bedrock. A turnkey voice-chat loop was not checked this round.
Video Understanding	Yes. Via file upload/YouTube	Partial. Video-capable models may be hosted. Bedrock itself is an inference platform, not a YouTube chat product.
Video Generation	Yes, requires plus plan. Veo video generation is available in the Gemini app and Flow.	No. Not a video generation product.
File Upload (PDF, DOCX)	Yes	Yes, requires plus plan. Knowledge Bases ingest documents (S3, etc.) for RAG.
Code Execution	Yes	Partial. Agents can call tools and Lambdas. No first-party Python sandbox in chat.
Audio Input	Yes	Partial. Speech models are listed. Bedrock is not a dedicated STT consumer app.
Canvas / Artifact Editor	Yes. Canvas in Gemini	No. Console playground, not a consumer artifacts canvas.
Screen Sharing / Computer Use	Yes	No. No computer-use desktop product.

Memory & Context — Google Gemini Wins

Memory & Context: Google Gemini compared with Amazon Bedrock
Feature	Google Gemini	Amazon Bedrock
Persistent Memory	No	Partial. Knowledge Bases and AgentCore session memory. You configure retention.
Large Context Window	Yes. 1M+ tokens	Unknown. Depends on the foundation model you invoke. No single Bedrock window.
Custom Instructions	Yes. Via Gems (custom AI personas)	Yes, requires plus plan. Guardrails, system prompts, and agent instructions in the console/API.
Conversation History	Yes	Partial. AgentCore sessions persist within configured limits. Stateless per InvokeModel call.

Integrations — Google Gemini Wins

Integrations: Google Gemini compared with Amazon Bedrock
Feature	Google Gemini	Amazon Bedrock
Web Search / Browsing	Yes	Partial. Agents can wire a search tool (e.g. via Lambda). Not a built-in cited search box.
Plugins / Extensions	No	Yes, requires plus plan. Action groups, Lambda tools, and third-party integrations for agents.
API Access	Yes, requires pro plan	Yes, requires plus plan. AWS SDK, InvokeModel, Agents, and Knowledge Bases APIs. Usage billing.
Zapier Integration	No	Unknown. No first-party Zapier listing was checked this round.
Custom GPTs / Bots	Yes. Gems (custom AI personas)	Yes, requires plus plan. Bedrock Agents and AgentCore are deployable custom agents.
Real-time Collaboration	Yes	No. IAM-shared console, not a multiplayer chat canvas.
Live Social Data Integration	No. No live social firehose in the Gemini app.	No. No live social firehose product.
Live Citation Mapping	Partial. Search grounding and Deep Research cite links in answers; not a citation-map canvas.	Partial. Knowledge Base RAG returns source chunks. Not Perplexity-style inline web citations.

Developer — Tie

Developer: Google Gemini compared with Amazon Bedrock
Feature	Google Gemini	Amazon Bedrock
Function Calling	Yes, requires pro plan	Yes, requires plus plan. Bedrock Agents use tool/action groups for function calling.
Streaming Responses	Yes	Yes, requires plus plan. InvokeModelWithResponseStream and Converse stream tokens.
Fine-Tuning	No	Yes, requires plus plan. Custom model fine-tuning is a listed Bedrock capability.
Embeddings API	Yes, requires pro plan	Yes, requires plus plan. Titan Embeddings and Knowledge Base vector indexes.
Structured Output (JSON)	Yes	Partial. Tool schemas and JSON mode depend on the model. Guardrails add structure.
Reasoning / Thinking Mode	Yes. Auto populated	Partial. Reasoning models (e.g. Claude extended thinking) can be hosted. No Bedrock-branded Deep Think toggle.
Local Execution	Partial. Gemini itself is closed, but the smaller Gemma models are downloadable and run locally.	No. Managed AWS inference. Distinct from Kiro local dev.
Open Weights	Partial. Gemini itself is closed; Gemma weights are downloadable.	Partial. Hosts some open models (e.g. Llama) alongside proprietary FMs.
Multi-Agent Orchestration	No. Gems are custom bots, not a user-facing multi-agent swarm in the consumer app.	Yes, requires plus plan. AgentCore supports multi-agent workflows and supervisor patterns.

Platforms — Google Gemini Wins

Platforms: Google Gemini compared with Amazon Bedrock
Feature	Google Gemini	Amazon Bedrock
Web App	Yes	Yes, requires plus plan. Bedrock console in the AWS Management Console.
iOS App	Yes	No. No consumer iOS app. AWS console is web-only.
Android App	Yes	No. No consumer Android app.
Desktop App	Yes, requires free plan. Native Gemini app for Apple Silicon Macs (macOS 15+, Option+Space). Windows gets Gemini in the Google app (Alt+Space). Both are free.	No. Console is browser-based, not a branded desktop app.
Chrome Extension	No	No. No Chrome extension.

Privacy — Tie

Privacy: Google Gemini compared with Amazon Bedrock
Feature	Google Gemini	Amazon Bedrock
GDPR Compliant	Yes	Yes, requires enterprise plan. AWS lists GDPR, HIPAA, and FedRAMP coverage for Bedrock.
Opt Out of Data Training	Yes	Yes, requires plus plan. AWS states it does not train on customer content submitted to Bedrock.
Enterprise Privacy Mode	Yes, requires enterprise plan	Yes, requires enterprise plan. VPC endpoints, KMS encryption, Guardrails, and enterprise AWS agreements.

Workspaces — Tie

Workspaces: Google Gemini compared with Amazon Bedrock
Feature	Google Gemini	Amazon Bedrock
Projects / Folders	Partial. Gems and conversation history	Partial. Knowledge Bases, agents, and guardrails are organized in the console. Not chat project folders.