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Dor Amir
Dor Amir

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The 600x LLM Price Gap Is Your Biggest Optimization Opportunity

#ai #opensource #python #llm

GPT-OSS-20B costs $0.05 per million input tokens. Grok-4 costs $30. That's a 600x spread. Even comparing production-grade models, GPT-5 mini at $0.25/M vs Claude Opus 4 at $5/M is a 20x difference.

Most teams pick one model and send everything to it. That's like shipping every package via overnight express, including the ones that could go ground.

The routing idea is simple

Not every prompt needs a frontier model. "Summarize this paragraph" and "Design a distributed system architecture" are fundamentally different tasks. One needs Claude Opus. The other works fine on GPT-5-mini at $0.10/M.

Smart routing classifies each prompt before it hits the API and sends it to the cheapest model that can handle it well.

What this looks like in practice

I built NadirClaw to do exactly this. It sits between your app and your LLM providers as an OpenAI-compatible proxy. The classification step takes about 10ms.

Here's what happens:

  1. Your app sends a request to NadirClaw (same format as OpenAI API)
  2. NadirClaw classifies the prompt complexity
  3. Simple tasks route to cheap models (Gemini Flash, GPT-5-mini, local Ollama)
  4. Complex tasks route to premium models (Claude Opus, GPT-5.2)

No code changes needed. Point your base URL at NadirClaw instead of OpenAI.

Real numbers

In testing across mixed workloads (coding, summarization, Q&A, data extraction):

  • 40-60% of prompts are "simple" and route to models costing 10-50x less
  • Overall cost reduction: 50-70% depending on workload mix
  • Quality degradation on routed prompts: negligible (simple prompts don't need frontier models)

The catch

Routing adds a classification step. That's ~10ms latency and a small amount of compute. For most applications, this is invisible. For latency-critical streaming, you might want to skip routing for known-complex paths.

Try it

NadirClaw is open source: https://github.com/doramirdor/NadirClaw

pip install nadirclaw
nadirclaw serve --port 8000
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Then point your OpenAI client at http://localhost:8000/v1 and watch your bill drop.

Disclosure: I'm the creator.

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