Large language models (LLMs) have become the foundation of many businesses, powering everything from customer service chatbots to advanced data analysis tools. However, the cost of running these models can quickly skyrocket if not managed efficiently, particularly when it comes to token usage. Each interaction with a language model, such as a request or response, consumes tokens — and the more tokens you use, the more you pay.
Let’s first understand what tokenization is and why it’s a crucial factor in managing costs in AI-driven applications.
Tokens are the building blocks of language models. When you input text into an AI system, the model doesn’t process the entire sentence as one big chunk. Instead, it breaks the text into smaller pieces called tokens. These tokens can be as small as a single character or as large as a word or phrase, depending on the language model.
For example, if you type “I love pizza,” this could be tokenised into three tokens: “I”, “love”, and “pizza.” The more complex your input, the more tokens are required. And for every token processed, there’s a cost involved, especially when dealing with large models like GPT or other LLMs.
When running applications powered by LLMs, you’re charged based on the number of tokens processed during each interaction. As businesses scale up their AI operations, these token costs can quickly escalate making efficiency in token usage a critical concern for organizations.
This is where Tumeryk can help save you money. Beyond providing critical security to your AI, Tumeryk helps you manage token usage, optimizing the performance of large language models (LLMs) AND significantly reducing costs.
How Tumeryk Saves You on Tokens
Tumeryk is an AI optimization tool that’s designed to make your LLM interactions more efficient, ensuring you use fewer tokens without sacrificing any performance or security. Here’s how Tumeryk achieves this:
1. Optimized Token Processing
Tumeryk AI intelligently manages the flow of information between users and your LLM. It pre-processes incoming requests to filter out unnecessary or redundant information, ensuring that only relevant data reaches the language model. This means that fewer tokens are required to handle the same amount of work, leading to significant (~30% or more) cost savings.
For instance, if your system receives long and complex queries, Tumeryk can trim and refine the inputs before they hit your LLM, reducing the token count without losing the essence of the request. By optimizing token usage at the input level, Tumeryk ensures that you’re not wasting tokens on irrelevant data.
2. Minimizing Token Overruns
In many cases, businesses find that their LLMs use more tokens than anticipated, leading to unexpected and sometimes staggering costs. This often happens due to poor input management or over-generation of responses. Tumeryk AI Guard helps mitigate this by carefully managing token usage at both input and output stages.
On the output side, Tumeryk can limit token-heavy responses, ensuring your LLM provides concise and accurate answers rather than overly verbose replies. This controlled response generation means your model is less likely to overrun token limits, keeping costs predictable and manageable.
3. Preventing Token Inflation Due to Malicious Activity
AI systems are not immune to malicious activities. In some cases, bad actors can send large volumes of requests to artificially inflate token usage, leading to higher costs for the business. Tumeryk provides robust protection against such malicious activities, ensuring that only legitimate queries are processed by your LLM.
By filtering out malicious requests before they ever reach your language models, Tumeryk prevents your token usage from spiraling out of control due to cyberattacks or bot traffic, thus protecting your budget as well as your data.
Ready to reduce your LLM token costs? Discover how Tumeryk can help you streamline token usage while securing your AI systems. Sign up now and take control of your GenAI app usage costs!
