The AI Tokens

Gemini 2.5 Pro Token Counter & Cost Calculator

Official pricing source: verifiedVerified on 2026-02-22

Compare Gemini 2.5 Pro

GPT-4o vs Gemini 2.5 Pro

Compare OpenAI's GPT-4o with Google's Gemini 2.5 Pro. Performance, pricing, and feature comparison.

Winner: GPT-4o

Claude Sonnet 4.6 vs Gemini Pro

Compare Anthropic's Claude Sonnet 4.6 with Google's Gemini Pro. Safety, reasoning, and cost analysis.

Winner: Claude Sonnet 4.6

Gemini 2.5 Pro vs Claude Sonnet 4.6

Premium AI model comparison: Google's Gemini 2.5 Pro vs Anthropic's Claude Sonnet 4.6. Advanced capabilities analysis.

It's a tie!

Pricing Breakdown

Official pricing source: verified (last checked 2026-02-22)

TierInput (USD / 1M)Output (USD / 1M)Cached input (USD / 1M)
≤ 200,000 input tokens1.2510.000.13
All usage2.5015.000.25

Example Costs

These are quick estimates using verified pricing bands (when available). Output tokens are the main driver here; use the calculator above for real prompt-based totals.

1K tokens
expected output: 1,000 tokens
Calculating…
10K tokens
expected output: 10,000 tokens
Calculating…
100K tokens
expected output: 100,000 tokens
Calculating…

Frequently Asked Questions

How much does Gemini 2.5 Pro cost?

Gemini 2.5 Pro pricing starts around 1.25 per 1M input tokens. See the official pricing source above for the latest updates.

What is Gemini 2.5 Pro best for?

Gemini 2.5 Pro is typically used for reasoning tasks, document analysis, structured output, and production API workloads.

Where can I find the official pricing for Gemini 2.5 Pro?

Use the "Official pricing source" link at the top of this page for the provider's most up-to-date pricing.

When to Use Gemini 2.5 Pro

🧠
Complex reasoning tasks
Multi-step problem solving and logical analysis
📄
Long document analysis
Processing large texts, reports, and research papers
⚙️
Production-grade structured output
JSON, XML, and formatted data generation
💻
High-quality code generation
Writing, debugging, and explaining code

Context Window

Gemini 2.5 Pro supports a maximum context size of 2,000,000 tokens.

This includes both input and output tokens combined. If your total tokens exceed this limit, the API may truncate input or return an error.

How to Reduce API Costs

🎯
Limit maximum output tokens
Set reasonable max_tokens to avoid unnecessary costs
✂️
Trim unnecessary system prompts
Remove verbose instructions and examples
📊
Use smaller models for simple tasks
Choose the right model size for your use case
💾
Cache responses when possible
Store and reuse responses for repeated queries

Words to Tokens Conversion

1,000 tokens ≈ 750–800 English words

Use the token counter above for exact model-specific calculation. Different languages and formats may vary.

Related Resources

Performance & Latency

Gemini 2.5 Pro is optimized for high-quality output. For lower latency workloads, consider smaller or "flash" variants where available.