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Optimize multi-model AI costs

Monitor and optimize costs across 200+ AI models through OpenRouter. Get intelligent model routing recommendations to reduce costs while maintaining quality.

Multi-Model Tracking

Monitor usage across 200+ AI models through OpenRouter's unified API

Cost Comparison

Compare costs across different models and providers in real-time

Model Optimization

Intelligent recommendations for model selection based on cost and performance

Simple integration

1

Connect OpenRouter Account

Securely connect your OpenRouter account using API key authentication

2

Enable Multi-Model Tracking

Configure monitoring across all available models and providers

3

Set Cost Thresholds

Configure alerts for model-specific and total spending limits

4

Get Smart Recommendations

Receive model routing recommendations based on cost and performance

OpenRouter Benefits

Model comparison

Compare costs and performance across all providers

Smart routing

Automatic routing to cost-effective models

Unified billing

Single dashboard for all AI spending

Model Categories We Optimize

Text Generation

40-70%

Optimize between GPT-4, Claude, Llama, and other text models based on task complexity

Code Generation

50-80%

Route coding tasks to the most cost-effective models like CodeLlama or DeepSeek

Image Generation

30-60%

Compare DALL-E, Midjourney, and Stable Diffusion costs for optimal image generation

Embeddings

60-85%

Use cost-effective embedding models for vector databases and semantic search

Vision Models

35-65%

Optimize image analysis between GPT-4V, Claude 3, and specialized vision models

Audio Processing

45-75%

Route speech and audio tasks to the most efficient models

SDK Integration

Monitor your OpenRouter usage with our SDK wrapper:

# Python SDK Integration
from deepcost import OpenRouterWrapper
import openai

# Wrap your OpenRouter client
client = OpenRouterWrapper(
    openrouter_api_key="your_openrouter_key",
    deepcost_api_key="your_deepcost_key"
)

# All API calls across models are tracked
response = client.chat.completions.create(
    model="anthropic/claude-3-sonnet",
    messages=[{"role": "user", "content": "Hello!"}]
)

Model Cost Comparison

Real-time cost comparison across popular models:

Text Generation

GPT-4$30/1M tokens
Claude 3 Sonnet$3/1M tokens
Llama 2 70B$0.8/1M tokens

Code Generation

GPT-4$30/1M tokens
CodeLlama 34B$0.8/1M tokens
DeepSeek Coder$0.14/1M tokens

Embeddings

OpenAI Ada v2$0.1/1M tokens
Voyage Large$0.12/1M tokens
BGE Large$0.03/1M tokens

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