Compare inference costs across GPT-5, Claude 4.5, Gemini 3, and more.
Now with agentic loops, caching, and reasoning tokens
In 2026, most AI applications use multi-step "agentic loops" rather than single prompts. Calculate costs for workflows like: "5 research steps + 1 summary step = 6 total steps."
Modern APIs (Anthropic, Gemini, OpenAI) offer context caching that reduces input costs by up to 90% for repeated data. Set your cache hit rate to see potential savings.
Reasoning models (like OpenAI's o-series) "think" before responding. These "thinking tokens" cost extra money and are often missed by older calculators. Enable reasoning to see the true cost.
Enable context caching to save up to 90% on repeated inputs
Visual comparison showing which model performs best for different use cases
| Model | Input Price | Output Price | Context | Total Cost | vs. Lowest |
|---|---|---|---|---|---|
Gemini 3 FlashGoogle | $0.07/1M | $0.30/1M | 1.0M | $0.004350 | Lowest |
o3 (Reasoning)OpenAI | $10.00/1M | $40.00/1M | 200.0K | $0.5800 | +$0.5756 (13233%) |
Copy-paste code to integrate Gemini 3 Flash into your application
import google.generativeai as genai
genai.configure(api_key="your-api-key")
model = genai.GenerativeModel('gemini-3-flash')
response = model.generate_content(
"Your prompt here",
generation_config={
"max_output_tokens": 2000
}
)
print(response.text)💡 Replace "your-api-key" with your actual API key. Adjust tokens and parameters as needed.
Compare pricing, features, and total cost of ownership between o3 (Reasoning) (OpenAI) and Gemini 3 Flash (Google). Find out which AI model offers the best value for your use case.
Gemini 3 Flash is more affordable
99% cheaper input pricing
Gemini 3 Flash has larger context
5.0x more context capacity
Gemini 3 Flash offers lower input pricing at $0.07 per 1M tokens compared to $10.00 for o3 (Reasoning). However, total costs depend on your usage patterns, output requirements, and whether you can leverage context caching. Use the calculator above to estimate costs for your specific use case.
o3 (Reasoning) supports up to 200,000 tokens, while Gemini 3 Flashsupports 1,000,000 tokens. Gemini 3 Flashcan handle longer documents and conversations without truncation, which is important for applications requiring extensive context.
Yes, many developers use multiple AI models for different tasks. You might use Gemini 3 Flashfor high-volume, cost-sensitive operations and o3 (Reasoning) for tasks requiring specific capabilities. The calculator above helps you compare costs across both models.
Both models support context caching, which can significantly reduce costs for repeated inputs. o3 (Reasoning) offers cached input at $2.50 per 1M tokens. Gemini 3 Flash offers cached input at $0.02 per 1M tokens.Additionally, optimize your prompts, use streaming for faster responses, and consider agentic workflows to minimize token usage.