Nano Banana (Gemini 2.5 Flash Image) vs Stable Diffusion 3.5

Nano Banana's $2.5/M output pricing reflects its multimodal capabilities (text+image->text+image) versus SD 3.5's pure text->image generation at $35/M output. The 50/100 score advantage comes from Nano Banana's 33K token context window enabling complex image understanding and generation workflows, while SD 3.5 operates with 0 token context as a stateless image generator.

At 10K images/month, SD 3.5 costs $350 versus Nano Banana's $25, making SD 3.5 economically unfeasible despite being open source. However, self-hosting SD 3.5 eliminates the $35/M output cost entirely, making it viable for high-volume use cases where Nano Banana's vision understanding, streaming, and JSON mode capabilities aren't required.

Nano Banana accepts image inputs alongside text prompts within its 33K context window, enabling iterative refinement and style transfer workflows impossible with SD 3.5's text-only input. This multimodal approach justifies the 3x score differential (50 vs 17) for applications requiring image-to-image transformations or visual question answering alongside generation.

SD 3.5 operates as a pure diffusion model mapping text embeddings directly to images without maintaining conversational state, hence the 0-token context. Nano Banana leverages Google's Gemini architecture supporting 33K input and 33K output tokens, enabling multi-turn image editing sessions and complex prompting strategies that contribute to its #5 ranking versus SD 3.5's #6 position.