Which AI Brain Powers Your Code? A Developer's Guide to the 3 Models in Antigravity IDE 2.0
A Developer's Guide to the 3 Models in Antigravity IDE 2.0
🎯 Three Models at a Glance
📊 Verified Specs Comparison
| Specification | GPT-OSS 120B | Claude Sonnet 4.6 | Gemini 3.5 Flash |
|---|---|---|---|
| Release Date | Aug 2025 | Feb 2026 | May 2026 |
| Architecture | MoE (Mixture-of-Experts) | Dense Transformer | Dense + Thinking Levels |
| Total Parameters | ~117B | Undisclosed | Undisclosed |
| Active Parameters | ~5.1B per forward pass | Undisclosed | Undisclosed |
| Context Window | 128K tokens | 1M tokens (Beta) | 1M tokens (GA) |
| Max Output | Undisclosed | Undisclosed | 65,536 tokens |
| Multimodal | Text-focused | Text + Image | Text · Image · Audio · Video |
| License | Apache 2.0 (commercial-free) | Anthropic ToS | Google ToS |
| Thinking Mode | Low/Medium/High effort | Adaptive Thinking (auto) | Thinking Levels (manual) |
| API Cost (In/Out) | Free (self-hosted) | $3 / $15 per 1M tokens | $1.5 / $9 per 1M tokens |
🤖 GPT-OSS 120B: The Open-Weight Powerhouse
Released by OpenAI in August 2025, this is the flagship of the open-weight AI world. The MoE architecture means the model's full 117B parameters serve as a knowledge base, but only ~5.1B activate per inference — enabling reasoning quality comparable to much larger models at a fraction of the compute cost. The MXFP4 quantization allows it to run on a single 80GB GPU (NVIDIA H100 or AMD MI300X). Full Chain-of-Thought access lets developers audit every reasoning step — a major advantage for regulated or high-stakes environments.
- Apache 2.0 — zero licensing restrictions for commercial use
- Self-hostable: your data never leaves your infrastructure
- Full CoT access for transparent reasoning audits
- Configurable reasoning effort (low/medium/high)
- Native agentic tools: function calling, search, code execution
- 128K context — smaller than the other two models
- Self-hosting requires significant GPU infrastructure
- 2026 benchmarks show newer models surpassing it in some tasks
- Limited multimodal support (image/audio)
🧠 Claude Sonnet 4.6: The Deep Reasoning Specialist
Released in February 2026, Sonnet 4.6 introduced Adaptive Thinking — the model dynamically calibrates how much reasoning effort to apply based on task complexity. A simple factual question gets a fast, direct answer. A complex architectural design problem triggers deep, structured deliberation. The 1M token context window (Beta) is a genuine game-changer for developers working with large codebases: you can analyze an entire repository in a single prompt without chunking. Notable benchmark gains in SWE-bench (coding) and OSWorld (computer use) make it the top choice for technical work requiring precision.
- Adaptive Thinking: excels at complex reasoning and coding
- 1M token context — analyze entire codebases at once
- Best-in-class natural language generation quality
- Top SWE-bench and OSWorld benchmark scores
- High accuracy for structured output (JSON, XML)
- Highest API cost of the three ($3/$15 per 1M tokens)
- Multimodal limited to text + image (no audio/video)
- Breaking change: assistant prefilling no longer supported
- No native real-time web search grounding
⚡ Gemini 3.5 Flash: The Multimodal Speed Champion
Launched in May 2026, Gemini 3.5 Flash made headlines immediately by outperforming its predecessor Gemini 3.1 Pro on reasoning benchmarks — including a CharXiv Reasoning score of 84.2% (vs. 83.2% for Pro). Its most distinctive capabilities are full-stack multimodality (text, images, audio, and video in a single prompt) and real-time Google Search grounding, which pulls live web data directly into responses. Thinking Levels let you dial between fast responses and deep reasoning on-demand. At $1.50/$9.00 per million tokens, it's also the most cost-efficient option for high-volume workloads.
- Full multimodal: text, image, audio, and video in one prompt
- Real-time Google Search grounding built-in
- Lowest API cost ($1.5/$9 per 1M tokens)
- 1M token context (GA, not Beta)
- Top scores on CharXiv, Terminal-Bench, MCP Atlas
- Max output capped at 65,536 tokens
- Long-form prose quality trails Claude in naturalness
- Optimized for Google ecosystem — non-Google integrations more complex
- Deep Think reasoning reserved for Gemini 3.5 Pro
🎯 Which Model for Which Job?
- Data privacy is non-negotiable
- Self-hosted / on-premise deployment
- Building open-source agentic pipelines
- Need full CoT reasoning transparency
- Cost is primary constraint
- Designing complex algorithms or architectures
- Analyzing large codebases end-to-end
- Writing technical docs or blog posts
- Debugging complex logic errors
- Long multi-turn context conversations
- Analyzing images, audio, or video files
- Real-time information lookup required
- Rapid prototyping and iteration
- High-volume, cost-sensitive workflows
- Integrating with Google Workspace / APIs
🔄 Switching Models in Antigravity IDE 2.0
Model switching in Antigravity IDE 2.0 is frictionless. Access the Model Selection dropdown from the chat interface header or settings panel at any time. Your conversation context is preserved across switches — meaning you can start a planning session with Claude's deep reasoning, then switch to Gemini Flash for a quick real-time lookup, all within the same conversation thread.
The Right Tool for Every Task
There is no universally "best" model — only the best model for the job in front of you. GPT-OSS 120B wins on freedom and data sovereignty. Claude Sonnet 4.6 wins on depth, reasoning quality, and long-context comprehension. Gemini 3.5 Flash wins on multimodal range, real-time grounding, and cost efficiency. Antigravity IDE 2.0 gives you all three. Use them strategically.
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