<aside> 💰 Cut your AI API bill by 50-90% without changing your code.

</aside>

Last month our team's AI API bill hit $1,850. This month it's $420. Same features, same quality. Here's exactly what we changed.

Strategy 1: Use an API Gateway with Built-in Discounts

The single biggest cost saver. Instead of paying OpenAI/Anthropic directly, route through a gateway that negotiates bulk pricing.

We switched to Crazyrouter and immediately saved ~55% on GPT-4 and Claude calls. For domestic models (DeepSeek, Qwen, GLM), savings are ~90%.

Strategy 2: Right-Size Your Models

Not every task needs GPT-4. Here's our model routing strategy:

• Classification, extraction, simple Q&A → GPT-4o-mini ($0.15/1M tokens)
• Complex reasoning, code generation → Claude Sonnet 4 ($3/1M tokens)
• Creative writing, nuanced analysis → GPT-4o ($2.50/1M tokens)
• Embeddings → text-embedding-3-small ($0.02/1M tokens)

Strategy 3: Cache Identical Requests

If you're sending the same prompt repeatedly (system prompts, common queries), cache the responses. We use Redis with a 1-hour TTL and cut 30% of our API calls.

import hashlib, redis, json

r = redis.Redis()

def cached_completion(messages, model="gpt-4o-mini"):
    key = hashlib.md5(json.dumps(messages).encode()).hexdigest()
    cached = r.get(key)
    if cached:
        return json.loads(cached)
    response = client.chat.completions.create(model=model, messages=messages)
    r.setex(key, 3600, json.dumps(response.to_dict()))
    return response

Strategy 4: Batch Processing

Instead of making 100 individual API calls, batch them. Most gateways support this and it reduces overhead significantly.

Results

• Before: $1,850/month (direct API, single model for everything)
• After: $420/month (Crazyrouter + model routing + caching)
• Savings: 77%