The Real Cost of AI APIs: What $1000/Month Actually Gets You

Let's talk about money. Specifically: how much will AI actually cost your startup?

The pricing pages for OpenAI, Anthropic, and Google are confusing. They talk about "tokens" and "1M tokens" and you're left wondering: okay, but how much does that mean for MY product?

Here's What $1000/Month Gets You

OpenAI GPT-4:

• ~100,000 chatbot conversations (assuming 200 tokens each)
• ~10,000 document summaries (2000 tokens each)
• ~50,000 customer support responses

Anthropic Claude:

• Similar to GPT-4, sometimes slightly cheaper
• Better for longer contexts (can handle 100K+ tokens)
• Often preferred for technical content

How to Estimate YOUR Costs

Step 1: Figure out your use case

• Chatbot? Customer support? Content generation?

Step 2: Estimate tokens per request

• Simple answer: ~200 tokens
• Full article: ~2000 tokens
• Complex analysis: ~5000+ tokens

Step 3: Calculate monthly volume

• How many users?
• How many requests per user?

Example: 1000 users, 10 requests/month each = 10,000 requests. At 200 tokens each = 2M tokens. At $10/1M tokens = $20/month.

Hidden Costs to Watch For

• Context window: More context = higher cost
• Failed requests: Still charged
• Embeddings: For RAG systems, add vector database costs
• Rate limits: May need higher tiers for scale

How to Reduce Costs

• Use smaller models for simple tasks (GPT-3.5 vs GPT-4)
• Cache common responses
• Optimize prompts to be shorter
• Use streaming to appear faster while using same tokens
• Implement rate limiting