The 2026 IDE Strategy: How to Choose Your AI Model in Antigravity

TL;DR: The era of sticking to one AI model for everything is over. In the new "Antigravity" IDE environment, your efficiency depends on Model Arbitrage—switching between models based on the complexity and modality of the task. My current stack? Claude Sonnet 4.5 (Thinking) is the daily workhorse. Gemini 3 Pro is the multimodal specialist. And when things get catastrophic, Claude Opus 4.5 is the "Break Glass in Case of Emergency" savant. Here is the breakdown of the hierarchy and three real-world case studies on how to apply them.

James here, CEO of Mercury Technology Solutions.

I’ve been spending a lot of time recently in Antigravity (the new AI-native IDE). The recurring question I get from my team is: "Which model should I actually use? There are too many versions."

I asked ChatGPT-5.1-Thinking to verify my intuition against the latest benchmarks, and the results align perfectly with my daily workflow.

If we rank them purely on Comprehensive Coding Capability (Architecture, Refactoring, Debugging, Context Window), the hierarchy for late 2025 looks like this:

1. Claude Opus 4.5 (Thinking) — The Architect
2. Claude Sonnet 4.5 (Thinking) / Gemini 3 Pro (High) — The Senior Engineers
3. Claude Sonnet 4.5 / Gemini 3 Pro (Low) — The Fast Iterators
4. GPT-OSS 120B (Medium) — The Open Source Backup

Here is the strategic breakdown of when to use what, followed by three specific use cases.

The Roster: Know Your Agents

1. The Heavy Artillery: Claude Opus 4.5 (Thinking)

• Role: The Staff Principal Engineer.
• Benchmarks: Dominated SWE-bench Verified (>80% accuracy). It beats Gemini 3 Pro and GPT-5.1 Codex on complex reasoning.
• Superpower: Deep reasoning steps. It doesn't just write code; it plans the architecture first. It creates fewer hallucinations on cross-file dependencies.
• Downside: Expensive and slow.
• Use When: You are stuck. You need to refactor a core legacy module. You need to debug a race condition across three microservices.

2. The Daily Driver: Claude Sonnet 4.5 (Thinking)

• Role: The Senior Developer.
• Benchmarks: ~77-82% on SWE-bench.
• Superpower: The "Agentic" sweet spot. It is excellent at calling tools, reading multiple files, and patching errors. The "Thinking" variant adds a layer of stability that makes it reliable for 90% of tasks.
• Use When: Writing feature skeletons, standard refactoring, or turning a PRD (Product Requirement Document) into initial code. This should be your default setting.

3. The Multimodal Specialist: Gemini 3 Pro (High)

• Role: The Frontend/UI Specialist.
• Benchmarks: Near perfect scores on Terminal-Bench and WebDev Arena.
• Superpower: It has a massive context window and native multimodal capabilities. It can "see" your UI screenshots and fix the CSS better than Claude.
• Use When: You are building web/app interfaces, need to debug based on a screenshot of an error, or are working with massive documentation (PDFs).

4. The Private Option: GPT-OSS 120B

• Role: The On-Premise Intern.
• Benchmarks: ~62% on SWE-bench.
• Use When: You have strict data privacy requirements that forbid cloud APIs, or you want to test an open-source workflow. Otherwise, it’s a backup.

Strategic Case Studies: How We Use Antigravity

The "One Model Fits All" approach is dead. Here is how we perform Model Arbitrage in real scenarios.

Case Study A: The "Vibe Coding" Sprint (PRD to Prototype)

Scenario: We need to build a new internal dashboard for tracking GPU usage. We have a rough text description (PRD) and a whiteboard sketch.

• Step 1 (Architecture): Switch to Claude Opus 4.5. Paste the PRD. Ask it to define the project structure, database schema, and API endpoints.
  • Why: Opus makes fewer structural mistakes at the start. A bad foundation ruins the project.
• Step 2 (Implementation): Switch to Claude Sonnet 4.5 (Thinking). Feed it the architecture from Step 1 and ask it to generate the boilerplate code and basic functions.
  • Why: Sonnet is faster and cheaper. It follows the Opus blueprint perfectly.
• Step 3 (UI Polish): Switch to Gemini 3 Pro (High). Upload a photo of the whiteboard sketch and a screenshot of the current (ugly) build. Ask it to: "Make the CSS match the sketch and fix the flexbox alignment."
  • Why: Gemini's vision capabilities are superior for visual debugging.

Case Study B: The "Legacy Hell" Refactor

Scenario: A critical Python service written three years ago is crashing. The code is spaghetti, with no documentation.

• The Move: Open Claude Opus 4.5 (Thinking) immediately.
• The Prompt: "Analyze these 15 files. There is a memory leak occurring during the data transformation step. Trace the execution flow and propose a refactor that preserves logic but fixes the leak."
• Why: Sonnet might offer a quick patch that breaks something else. Opus has the "reasoning depth" to hold the entire complex mental model of the 15 files in its "head" before suggesting a surgical fix. It’s worth the extra cost.

Case Study C: The "Frontend Component" Factory

Scenario: We need to build 50 different React components for a design system (buttons, modals, sliders) based on a Figma file.

• The Move: Gemini 3 Pro (High) or Sonnet 4.5 (Standard).
• Why: These are isolated, low-complexity tasks. Using Opus here is burning money. Using the "Thinking" models is wasting time. Standard Sonnet or Gemini High can churn these out rapidly with high accuracy.

Conclusion: Your Stack is Your Leverage

In the Antigravity era, you are not just a coder; you are a Model Orchestrator.

My default config for 2026:

• Default: Claude Sonnet 4.5 (Thinking)
• UI/Visuals: Gemini 3 Pro (High)
• Crisis/Architecture: Claude Opus 4.5 (Thinking)

Stop treating AI models like a religion where you only worship one. Treat them like a toolkit. You don't use a sledgehammer to hang a picture frame, and you don't use a screwdriver to demolish a wall.

Mercury Technology Solutions: Accelerate Digitality.