What are reasoning tokens in OpenAI o1 ?

Internal thoughts the model generates before answering — billed like output tokens, invisible to you, can multiply costs 5x+.

How to reduce LLM output token costs?

Prompt concisely, set max_tokens limits, batch requests, avoid verbose instructions.

Input vs output tokens pricing comparison?

Inputs: $2.50-$5/million. Outputs: $10-$20/million. Reasoning: output rates, hidden.

🤖 AI & Machine Learning

The Hidden Token Trap: Why Reasoning Tokens Are Bleeding Your AI Budget Dry

Staring at your LLM bill? That 'reasoning' line item you ignored is why it's 10x what you expected. Here's the cynical truth behind input, output, and those sneaky hidden thoughts.

Open Source Beat Apr 11, 2026 4 min read

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Comparison chart of input, output, and reasoning token pricing across OpenAI, Anthropic, and Google LLMs

⚡ Key Takeaways

Output and reasoning tokens cost 3-4x more than input due to sequential generation vs parallel processing. 𝕏
Reasoning tokens are invisible 'thinking' billed at premium rates — a potential 5-10x bill multiplier. 𝕏
Optimize by caching prompts, limiting verbosity, and monitoring breakdowns to slash AI costs. 𝕏

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#OpenAI costs #OpenAI o1 #input output tokens #input-tokens #llm-pricing #output-tokens #reasoning-tokens

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Originally reported by Dev.to

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