Batch API Cost-Effective for Multi-File Code Changes

A developer on r/ClaudeAI shared their experience using batch processing with Claude Sonnet and Opus for coding tasks, highlighting its cost-effectiveness and workflow.

Key Details from the Source

The developer achieved significant code changes across over 30 different files, generating around 3,000 lines of code for approximately £2. They initially focused on RAG (Retrieval-Augmented Generation) but found it unnecessary for their use case.

Their workflow involved:

• Using Claude Opus to determine which files were needed for large requests
• Employing a two-step batch process with relatively simple prompts
• Using Repomix to gather content to send to the models
• Utilizing Minimax m2.5/Qwen Coder to clean up issues from Sonnet after search/replace operations

Specific cost examples mentioned:

• First prompt: $0.30
• Second prompt with code changes: $1.42
• Minimax cleanup costs: described as "barely anything"

The developer completed API development and replaced all mock data tables in their Flutter app with actual API data. They noted learning about caching across multiple prompts, describing the ability to cache certain parts of batches across different requests as "a game changer."

Their model usage strategy evolved:

• Originally used Opus for planning and Sonnet for implementation
• Later experimented with GPT for planning, then feeding that output to Sonnet
• Found this approach better for token efficiency than using Opus throughout

The developer acknowledged making mistakes initially, particularly with caching across multiple prompts, and invited questions about their experience.