---
title: "Gemini 3 Pro Added to Database AI Suite. Tested Against Claude Sonnet 4.5 and GPT-5.1.Results: Claude still leads. GPT-5.1 is solid. Gemini 3 Pro lands third."
slug: gemini-3-pro-added-to-database-ai-suite-tested-against-claude-sonnet-4-5-and-gpt-5-1-results-claud
date_published: 2025-11-21T04:56:27.578Z
original_url: https://www.tigzig.com/post/gemini-3-pro-added-to-database-ai-suite-tested-against-claude-sonnet-4-5-and-gpt-5-1-results-claud
source: migrated
processed_at: 2025-12-03T10:03:34.929302Z
---

# Gemini 3 Pro Added to Database AI Suite. Tested Against Claude Sonnet 4.5 and GPT-5.1.Results: Claude still leads. GPT-5.1 is solid. Gemini 3 Pro lands third.

![Image 1: ree](https://static.wixstatic.com/media/ef0c19_ddbadee2e6a6496496c67dcb517bbf1b~mv2.png/v1/fill/w_740,h_925,al_c,q_90,usm_0.66_1.00_0.01,enc_avif,quality_auto/ef0c19_ddbadee2e6a6496496c67dcb517bbf1b~mv2.png)

## Performance Scores

Multi-step database analysis workflows:

* Claude Sonnet 4.5: 115
* GPT-5.1: 100
* Gemini 3 Pro: 90
* 90-tier: Gemini 2.5 Pro, GPT-4.1, KIMI 2 Thinking
* 85-tier: Gemini 2.5 Flash, Qwen 3 Max, GLM 4.6, DeepSeek R1
* 80-tier: Gemini 2.0 Flash

## Model Findings

* Claude Sonnet 4.5: Creates multiple segmentation variables beyond the prompt. Quality leader.
* GPT-5.1: Strong. Token bloat gone vs GPT-5. Clear second.
* Gemini 3 Pro: Similar to Gemini 2.5 Pro. Better explanations, same output quality. Doesn't match top two.

## What Was Tested

Credit card analysis: 1M customer + 10M transaction tables (AWS RDS MySQL). Multi-step workflow - plan, summarize, create derived variables, merge, segment profiles.

Weighted ranking of Indian credit card issuers from RBI data (Postgres).

## Practical Choices

* High quality → Claude Sonnet 4.5
* Balance → GPT-4.1
* Low cost- great value→ Gemini 2.5 / 2.0 Flash

## Cost Breakdown

### Planning vs Execution

Single iteration: reasoning LLM runs once (20% cost), execution agent runs 7-10 queries with debugging (80% cost).

### Reasoning / Planning Cost (Per 100 Questions)

* High: Claude, GPT-5.1, Gemini 3 Pro (approx. $7.00)
* Mid: GPT-4.1, KIMI 2, Qwen, GLM, DeepSeek (approx. $2.50)
* Budget: Gemini 2.5 Flash (approx. $1.50), Gemini 2.0 Flash ($0.30)

Avoid: Gemini 2.5 Pro ($10) and GPT-5 ($15) - token bloat.

### Execution Cost (Per 100 Questions)

* Advanced analysis: approx. $12.50 (GPT-4.1, consistent across reasoning models)
* Single-step: $0.40 (GPT-4.1-mini) to approx. $3.50 (GPT-5.1)

I use OpenAI for SQL execution - more reliable. Multi-step workflows multiply costs fast. Use only when needed.

These costs relate to my typical uses. Your numbers will vary based on context, architecture & output volume. Always test with your use case. Always check actual billing, not token based estimates.

## DATS-4: Database AI Suite- v4

Remote database AI app. Postgres or MySQL. Single-step queries or multi-step analysis. Python charts, table upload, PDF reports. Open source, live, free.

### Try It

Use Sample button. Data loads to temp Postgres. Or connect your database.

Public app routes through my backend - sandbox only. Deploy on your servers for live work

## Resources

* Database AI Field guide- usage, architecture, process flows
* Previous post: GPT-5.1 + KIMI 2 evaluation with short video
* Posts & guides - AI for Analytics: [tigzig.com](http://tigzig.com/)

## Direct access to the main database AI apps:

* **ChatGPT + Your Database** (connect any Postgres/MySQL): [ChatGPT here](https://app.tigzig.com/database-landing)
* **ChatGPT + Fixed Data** (Simultaneous connection across 3 Databases): [ChatGPT here](https://app.tigzig.com/sql-rooms)

## Related resources - Database AI

* **Implementing Database AI: Field Guide** - 49-page PDF - architecture, agent setups, cost analysis - [Read Here](https://lnkd.in/geHAn2uf)
* **In-Browser Database AI** - 1.5 GB files: process locally with DuckDB - [Read here](https://app.tigzig.com/database-landing)
* **10 Options for Talking to your databases** - 10 micro-apps across 5 categories - Remote, In-Browser, ChatGPT, Voice, Rapid Deploy - [Read here](https://lnkd.in/gzkeBQrf)