Glossary

What Is Token Cost?

Token cost is the pricing unit for LLM API usage, charged per input and output token processed by the model.

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Definition

Token cost refers to the price charged by LLM providers for processing text through their models. Text is split into tokens (roughly 3/4 of a word in English), and providers charge separately for input tokens (your prompt) and output tokens (the model's response). Costs are typically quoted per million tokens and vary dramatically between models — from $0.10/M for lightweight models to $60/M for frontier reasoning models.

How token pricing works

Every API call processes input tokens (your prompt, system message, and conversation history) and generates output tokens (the model's response). Providers charge different rates for each. For example, GPT-5.2 charges roughly $2.50 per million input tokens and $10 per million output tokens. Long conversations accumulate input costs because the full history is sent with each turn. Understanding this structure is key to controlling costs — shorter system prompts and conversation summaries can cut costs substantially.

Cost differences between models

Token costs vary by 100x or more across models. Frontier models like Claude Opus 4.6 and GPT-5.2 charge premium rates for maximum capability. Mid-tier models like Claude Sonnet 4.5 and Gemini 3 Flash offer a strong quality/cost balance. Budget models like DeepSeek V3 and Llama 4 Maverick deliver surprisingly good results at a fraction of the cost. Free models exist for prototyping. The right choice depends on your quality requirements and volume.

Reducing token costs with LLMWise

LLMWise helps reduce token costs through Auto routing (which selects the cheapest model that meets quality thresholds), cost optimization policies (which analyze your usage patterns and recommend cheaper models), and BYOK (which lets you use your own provider keys at direct-to-provider pricing). The credit system abstracts away per-token math: 1 credit = 1 chat request regardless of the model chosen.

How LLMWise implements this

LLMWise gives you five orchestration modes — Chat, Compare, Blend, Judge, and Mesh — with built-in optimization policy, failover routing, and replay lab. No monthly subscription is required and paid credits do not expire.

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Evidence snapshot

What Is Token Cost? concept coverage

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intro + practical implementation
Related concepts
what is llm routingwhat is llm gatewaywhat is model orchestration

Common questions

How much does it cost to use an LLM API?
Costs range from free (for lightweight open-source models) to $60+ per million tokens for frontier reasoning models. A typical production application using a mid-tier model like GPT-5.2 costs $2.50-$10 per million tokens. LLMWise simplifies this with a credit system: 100 credits per dollar, 1 credit per chat request.
What is a token in AI?
A token is the basic unit of text that LLMs process. In English, one token is roughly 3/4 of a word (or about 4 characters). The word 'hamburger' is 3 tokens. Providers charge per token for both input (your prompt) and output (the model's response). Understanding tokens helps you estimate and control API costs.
How can I reduce my LLM API costs?
Use a routing layer like LLMWise Auto to send simple requests to cheaper models. Shorten system prompts and summarize conversation history. Use prompt caching where available. Consider BYOK to use your own provider keys at direct pricing. LLMWise cost optimization policies analyze your usage and recommend cheaper alternatives automatically.
Are input tokens more expensive than output tokens?
Usually the opposite — output tokens are 2-4x more expensive than input tokens for most models. This is because generating text requires more compute than reading it. To minimize costs, keep your prompts concise but focus especially on reducing unnecessary output length through clear instructions.

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Related pages
What Is a Context Window?What Is a Multi-Model API?What Is BYOK (Bring Your Own Key)?What Is LLM Routing?What Is Model Orchestration?What Is an LLM Gateway?