Anthropic API is too expensive for my use case

If Anthropic’s API feels too expensive, you’ve got a few practical paths:

1. Use a cheaper model/provider

   • OpenAI smaller models, Google Gemini, Mistral, Cohere, or OpenRouter-hosted options.
   • For many tasks, a smaller model is “good enough” with the right prompt.

2. Reduce token usage

   • Shorten system prompts and examples.
   • Trim chat history aggressively.
   • Summarize older context instead of sending it all.
   • Lower max_tokens to what you actually need.
   • Avoid asking for verbose outputs unless necessary.

3. Route by task

   • Use a cheap model for classification, extraction, rewriting.
   • Reserve a stronger model only for hard cases.
   • This hybrid approach often cuts cost a lot.

4. Consider self-hosted/open-source models

   • Llama, Qwen, Mistral, DeepSeek variants depending on your hardware and latency needs.
   • Best if you have predictable traffic and can manage infra.

5. Cache responses

   • Cache repeated prompts/results.
   • Especially useful for FAQ, templates, and deterministic workflows.

6. Batch or async where possible

   • If your workflow can tolerate delay, batch requests or process offline to improve efficiency.

If you want, I can help you:

• estimate costs for your current usage,
• redesign your prompts to use fewer tokens,
• or suggest a cheaper model stack for your exact use case.