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LLM ComparisonGPT-5Nano Banana 2

GPT-5 vs Nano Banana 2

Compare GPT-5 and Nano Banana 2. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5Nano Banana 2
ProviderOpenAIGoogle
Model Typetextimage
Context Window400,000 tokensN/A
Input Cost
$1.25/ 1M tokens
N/A
Output Cost
$10.00/ 1M tokens
N/A

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Strengths & Best Use Cases

GPT-5

OpenAI

1. High reasoning capability

  • Designed for intelligent reasoning across complex domains.
  • Supports reasoning tokens and adjustable reasoning effort.

2. Strong coding and agentic performance

  • Optimized for multi-step coding tasks, tool-use chains, and agent workflows.
  • Handles complex logic, planning, and structured problem solving reliably.

3. Multimodal input

  • Accepts text + image as input.
  • Produces text outputs with strong instruction following.

4. Extensive tool support

  • Works with Web Search, File Search, Image Generation (as a tool), Code Interpreter, MCP, and more.
  • Integrated across Chat Completions, Responses API, Realtime, Assistants, Batch, Embeddings, etc.

Nano Banana 2

Google

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.