GPT-5 Nano vs Gemini 1.5 Flash
Compare GPT-5 Nano and Gemini 1.5 Flash. Find out which model is better for your specific use case and requirements.
Model Comparison
| Feature | GPT-5 Nano | Gemini 1.5 Flash |
|---|---|---|
| Provider | OpenAI | |
| Model Type | text | text |
| Context Window | 400,000 tokens | 1,000,000 tokens |
| Input Cost | $0.05/ 1M tokens | $0.07/ 1M tokens |
| Output Cost | $0.40/ 1M tokens | $0.30/ 1M tokens |
Strengths & Best Use Cases
GPT-5 Nano
OpenAI1. Extremely fast performance
- Fastest model in the GPT-5 family.
- Great for real-time workflows, rapid responses, and high-throughput systems.
2. Most cost-efficient GPT-5 model
- Lowest input and output token costs.
- Suitable for large-scale or budget-sensitive applications.
3. Ideal for lightweight, well-scoped tasks
- Excels at summarization, classification, text extraction, and simple logic tasks.
- Best used when tasks are narrow and well-defined.
4. Multimodal input
- Accepts text + image as input.
- Outputs text only.
5. Broad tool support
- Supports Web Search, File Search, Image Generation (as a tool), Code Interpreter, and MCP.
- (Does not support Computer Use.)
Gemini 1.5 Flash
Google1. Extremely fast and cost-efficient
- Designed for ultra-low latency inference.
- Handles high-throughput real-time applications and large-scale pipelines.
2. Strong multimodal capabilities
- Accepts text, images, audio, video, and PDFs.
- Efficient cross-modal understanding suitable for classification, extraction, and captioning.
3. Excellent for long-context tasks
- Supports up to 1M tokens, enabling analysis of long documents, transcripts, and entire codebases.
- Performs well on long-context translation and summarization.
4. Optimized for production workloads
- Low operational cost and fast inference make it ideal for enterprise automation.
- Great for chatbots, customer support systems, and background agent tasks.
5. High throughput with scalable rate limits
- Flash variants support extremely high RPM for high-traffic environments.
6. Reliable performance on everyday tasks
- Good at chat, rewriting, transcription, extraction, and structured reasoning.
- More efficient than Pro for tasks that don't require deep reasoning.
7. Ideal for multimodal high-volume apps
- Strong performance on captioning, OCR-style extraction, audio transcription, and video understanding.
8. Designed for developer workflows
- Supports function calling, structured output, and integration with the Gemini API and Vertex AI.
Try These Prompts
Discover AI prompts that work great with these models. Use them to build powerful AI tools on Appaca.
Best for GPT-5 Nano
textCreate Discovery Questions (Interrogatories + RFPs + RFAs)
Generate clear, organized discovery questions and requests tailored to a specific legal issue and case theory.
Create Wealth Plan
Create a comprehensive wealth plan with this AI prompt, embodying Victor Sterling's analytical approach to strategic investing and wealth management.
Legal Contract Summarizer
Summarize complex legal contracts into plain English to understand key terms, obligations, and risks.
Best for Gemini 1.5 Flash
textCustomer Feedback Loop (Insights → Messaging)
Design a customer feedback loop to track evolving persona challenges and preferences, informing marketing strategy and USP refinement.
Lead Generation Strategy (USP-to-Offer Engine)
Build a lead generation strategy that turns your USP into compelling offers and acquisition channels tailored to persona challenges.
Thought Leadership Series (Challenges → Framework)
Develop a thought leadership series that addresses persona challenges and showcases your expertise and USP.
Use Appaca to make AI tools powered by GPT-5 Nano or Gemini 1.5 Flash
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