1. Strongest Codex Model for Agentic Engineering

• OpenAI positions GPT-5.3 Codex as its most capable agentic coding model to date.
• Built for long-horizon software engineering tasks that require planning, iteration, and reliable code transformation across files.

2. Configurable Reasoning + Multimodal Input

• Supports configurable reasoning effort from low to xhigh so teams can trade off depth against latency.
• Accepts both text and image inputs while producing text output.

3. Large Context for Real Codebases

• 400 k token context window helps it work across larger repositories, implementation plans, and supporting documentation.
• Allows up to 128 k output tokens for longer code generations, patches, and technical write-ups.

4. Current Knowledge for Modern Dev Workflows

• Knowledge cut-off of Aug 31 2025 keeps it aligned with newer frameworks, libraries, and tooling.
• Supports streaming, function calling, and structured outputs for agent-style coding workflows.

1. High-efficiency counterpart to Gemini 3 Pro Image

• Google describes Nano Banana 2 as the high-efficiency counterpart to Gemini 3 Pro Image.
• Optimized for speed and high-volume developer use cases rather than maximum pro-grade fidelity.

2. Native image generation + understanding

• Accepts text and image inputs and can output both text and images in a conversational workflow.
• Useful for quick iteration, editing, remixing, and interactive visual applications.

3. Strong throughput with practical image controls

• Supports up to 14 input images per prompt, 128 k input tokens, and 32,768 output tokens.
• Handles multiple aspect ratios and can generate or edit images while keeping latency and cost lower than higher-end image models.

4. Grounded, developer-friendly image workflows

• Supports Google Search grounding and Content Credentials (C2PA) for image outputs.
• All generated images include SynthID watermarking as part of Google's native image stack.