#+TITLE: Token Management & Model Optimization Research
#+author: Amero Garcia
#+created: [2026-03-16 Mon 14:28]
#+DATE: 2026-03-04
#+FILETAGS: :research:token:optimization:models

* Token Management Strategy Research

** Initial Findings

*** OpenRouter Free Tier
- URL: https://openrouter.ai/collections/free-models
- Providers moving from free to paid-only models
- Belief: "Free models play crucial role in democratizing access"

*** Google AI Studio (Gemini)
- Free tier available
- Limits: 60 requests/minute, 300K tokens/day
- No credit card required
- Every API key gets these limits

** Research Questions

1. Which providers offer free or low-cost tiers?
2. What are the rate limits and quotas?
3. Which models are best for which use cases?
4. How to optimize context windows?
5. What is the cost per token breakdown?

** To Research Further

| Provider | Free Tier | Paid Tier | Best For |
|----------|-----------|-----------|----------|
| Google Gemini | 300K tokens/day | Pay per use? | General, coding |
| OpenRouter | Varies by model | Per-request | Routing, variety |
| OpenAI | ? | ? | GPT-4 quality |
| Anthropic | ? | ? | Claude capabilities |
| Mistral | ? | ? | Open weights |
| Local | Hardware cost | Free | Privacy, control |

** Token Optimization Strategies to Explore

1. *Tiered Model Usage*
   - Simple tasks: Fast/cheap models
   - Complex tasks: Stronger models
   - Fallback: Lower tier if higher fails

2. *Context Compression*
   - Summarize long contexts
   - Use RAG instead of full context
   - Prune old conversation

3. *Caching*
   - Cache common responses
   - Reuse embeddings
   - Batch requests

4. *Hybrid Approach*
   - Local models for simple queries
   - Cloud APIs for complex tasks
   - Manual review for critical outputs

** X Account Access

*Pending:* X account access via Google login
*Blocker:* Requires OTP from user per security rule (SOUL.md)
*Action needed:* User provides OTP, I complete OAuth, access bookmarks