Head to head

Gemini vs Make

No endless tables — just the differences that matter, and a clear call. Pick two tools and see who takes it.

The facts, side by side

Gemini Make

Pricing

GeminiFreemium

MakeFreemium

Rating

Gemini4.3

Make4.1

Description

GeminiGoogle's multimodal AI assistant built on the Gemini 3.1 architecture, notable for deep Google Workspace integration and 77.1% on the ARC-AGI-2 benchmark. Available across free, AI Pro ($20/mo), and Ultra ($250/mo) tiers with progressively larger context and model access. Strongest competitor to ChatGPT for users already in the Google ecosystem.

MakeVisual automation platform (formerly Integromat) known for a scenario builder that makes data transformation and routing logic easier to visualize than Zapier's linear flow model. At $9-16/mo for 10,000-40,000 operations, it sits between free tools and enterprise platforms. Strong for teams doing complex multi-branch data processing without writing code.

Gemini 3.1 Pro model with multimodal input (text, image, audio, video)

Gemini

Make

77.1% score on ARC-AGI-2 abstract reasoning benchmark

Gemini

Make

Deep integration with Gmail, Docs, Sheets, Drive, and Meet

Gemini

Make

NotebookLM integration for research with source citations

Gemini

Make

Google Search grounding for real-time factual responses

Gemini

Make

Code execution sandbox for Python data analysis

Gemini

Make

AI Ultra tier with access to Gemini 3.1 Ultra model

Gemini

Make

Gemini API with 2M token context for developers

Gemini

Make

Visual scenario builder with non-linear, branching workflow visualization

Gemini

Make

2,000+ app integrations including HTTP/REST and webhooks for custom APIs

Gemini

Make

Advanced router modules for conditional branching and data filtering

Gemini

Make

Data store: built-in lightweight database for state persistence between scenarios

Gemini

Make

JSON/XML parsing and transformation with no-code tools

Gemini

Make

Scenario scheduling: minute-level granularity on triggers

Gemini

Make

Error handling routes for automatic retry and failure notification

Gemini

Make

Team features: shared scenarios, scenario logs, version history

Gemini

Make

Pros

Gemini

Google Search grounding provides current information without hallucination risk of pure model outputs
Native Google Workspace integration means no copy-pasting between tools for Docs/Sheets users
ARC-AGI-2 score of 77.1% leads all commercial models on abstract reasoning tasks
NotebookLM included in AI Pro tier provides citation-backed research at no extra cost

Make

Non-linear visual builder is significantly clearer than Zapier for workflows with multiple branches and conditions
Operations-based pricing means 1 automation with 5 steps costs 5 ops — often cheaper than per-task Zapier pricing
Data Store allows state to persist between runs without an external database for simple key-value use cases
Free tier includes 1,000 operations/month — enough for testing before committing to a paid plan

Cons

Gemini

AI Ultra at $250/mo is 12.5x the price of Pro with modest real-world gains for most use cases
Gemini 3.1 Ultra access is gated to Ultra tier; Pro users get 3.1 Pro which lags on creative tasks
Google Workspace integration requires organizational admin approval, blocking individual use in enterprise
Voice mode is less natural than ChatGPT's real-time voice in head-to-head comparisons
Data privacy terms differ from ChatGPT; free tier data may be used for model training by default

Make

AI node support is limited compared to n8n — building LLM pipelines requires more manual HTTP module work
Scenario builder becomes visually complex (hard to read) on workflows with 30+ modules
Free tier requires manual scenario activation — paid plan required for scheduled automatic runs
No self-hosting option — all data flows through Make's cloud infrastructure
Cost scales linearly with operation count, not workflow count; high-frequency scenarios become expensive at $9/mo base

Tool	Gemini	Make
Pricing	Freemium	Freemium
Rating	4.3	4.1
Category	AI Assistants	Workflow Automation
Description	Google's multimodal AI assistant built on the Gemini 3.1 architecture, notable for deep Google Workspace integration and 77.1% on the ARC-AGI-2 benchmark. Available across free, AI Pro ($20/mo), and Ultra ($250/mo) tiers with progressively larger context and model access. Strongest competitor to ChatGPT for users already in the Google ecosystem.	Visual automation platform (formerly Integromat) known for a scenario builder that makes data transformation and routing logic easier to visualize than Zapier's linear flow model. At $9-16/mo for 10,000-40,000 operations, it sits between free tools and enterprise platforms. Strong for teams doing complex multi-branch data processing without writing code.
Gemini 3.1 Pro model with multimodal input (text, image, audio, video)	Supported	Not supported
77.1% score on ARC-AGI-2 abstract reasoning benchmark	Supported	Not supported
Deep integration with Gmail, Docs, Sheets, Drive, and Meet	Supported	Not supported
NotebookLM integration for research with source citations	Supported	Not supported
Google Search grounding for real-time factual responses	Supported	Not supported
Code execution sandbox for Python data analysis	Supported	Not supported
AI Ultra tier with access to Gemini 3.1 Ultra model	Supported	Not supported
Gemini API with 2M token context for developers	Supported	Not supported
Visual scenario builder with non-linear, branching workflow visualization	Not supported	Supported
2,000+ app integrations including HTTP/REST and webhooks for custom APIs	Not supported	Supported
Advanced router modules for conditional branching and data filtering	Not supported	Supported
Data store: built-in lightweight database for state persistence between scenarios	Not supported	Supported
JSON/XML parsing and transformation with no-code tools	Not supported	Supported
Scenario scheduling: minute-level granularity on triggers	Not supported	Supported
Error handling routes for automatic retry and failure notification	Not supported	Supported
Team features: shared scenarios, scenario logs, version history	Not supported	Supported
Pros	Google Search grounding provides current information without hallucination risk of pure model outputs Native Google Workspace integration means no copy-pasting between tools for Docs/Sheets users ARC-AGI-2 score of 77.1% leads all commercial models on abstract reasoning tasks NotebookLM included in AI Pro tier provides citation-backed research at no extra cost	Non-linear visual builder is significantly clearer than Zapier for workflows with multiple branches and conditions Operations-based pricing means 1 automation with 5 steps costs 5 ops — often cheaper than per-task Zapier pricing Data Store allows state to persist between runs without an external database for simple key-value use cases Free tier includes 1,000 operations/month — enough for testing before committing to a paid plan
Cons	AI Ultra at $250/mo is 12.5x the price of Pro with modest real-world gains for most use cases Gemini 3.1 Ultra access is gated to Ultra tier; Pro users get 3.1 Pro which lags on creative tasks Google Workspace integration requires organizational admin approval, blocking individual use in enterprise Voice mode is less natural than ChatGPT's real-time voice in head-to-head comparisons Data privacy terms differ from ChatGPT; free tier data may be used for model training by default	AI node support is limited compared to n8n — building LLM pipelines requires more manual HTTP module work Scenario builder becomes visually complex (hard to read) on workflows with 30+ modules Free tier requires manual scenario activation — paid plan required for scheduled automatic runs No self-hosting option — all data flows through Make's cloud infrastructure Cost scales linearly with operation count, not workflow count; high-frequency scenarios become expensive at $9/mo base
Website	Visit	Visit

The facts, side by side

Pricing

Rating

Category

Description

Gemini 3.1 Pro model with multimodal input (text, image, audio, video)

77.1% score on ARC-AGI-2 abstract reasoning benchmark

Deep integration with Gmail, Docs, Sheets, Drive, and Meet

NotebookLM integration for research with source citations

Google Search grounding for real-time factual responses

Code execution sandbox for Python data analysis

AI Ultra tier with access to Gemini 3.1 Ultra model

Gemini API with 2M token context for developers

Visual scenario builder with non-linear, branching workflow visualization

2,000+ app integrations including HTTP/REST and webhooks for custom APIs

Advanced router modules for conditional branching and data filtering

Data store: built-in lightweight database for state persistence between scenarios

JSON/XML parsing and transformation with no-code tools

Scenario scheduling: minute-level granularity on triggers

Error handling routes for automatic retry and failure notification

Team features: shared scenarios, scenario logs, version history

Pros

Cons