Researched and written by Jan Hofmeister and Roman Civin. Introduction If you're overwhelmed by all the information on different machine translation (MT) options and cost factors, don't stress, we've got you. But don't just take our word for it - use the handy interactive calculator tool to break down costs based on your unique needs. Plug in your numbers and get a quick custom cost analysis - using a comparable denominator. To understand machine translation costs, let’s break it down to simple options: Generic MT engines are easy to use, but quality varies. MT traditionally customized via regular pre-training tailored to your business slang gives better translations but costs more upfront. Adaptive MT automatically improves over time based on your feedback and is more flexible than custom engines. Large language models (LLMs) are cutting-edge but still new and need strong guidance for best results. Combining LLMs with neural MT (NMT) is where it's at for top efficiency. Fixed and variable costs must be considered when choosing the right machine translation method for your budget. If more questions arise, don't hesitate to seek Nimdzi's expert advice to optimize your strategy. Insights Traditional customized NMT is facing a challenge because of its scaling limitations. Adaptive MT is the current frontier. Companies often spend more on customized NMT than they are aware of. To comprehend the cost implications of MT, stakeholders must consider a spectrum of fixed and variable expenses. The complexity associated with customized NMT is justified only in cases where it cannot be replaced by newer solutions. Think fixed AND variable costs Explaining the costs of MT engine customization involves both fixed and variable costs. Fixed costs include domain-specific content translation, language count, engine training frequency, and ongoing management expenses. Variable costs are tied to the annual translation volume. Essentially, MT customization costs go beyond the direct training fees, covering a spectrum of related activities and requiring a significant resource investment for comprehensive management. Guidelines How to use the MT cost calculator: Whether you're an experienced MT user or new to estimating the cost of customized NMT, this tool is designed to help you compare MT solutions effectively. By breaking down various cost factors and providing insights per 1000 source words, you can make informed decisions about your MT strategy. It is an active thinking process to check and ensure that you have included all relevant variables and costs in the calculator and that you estimate these realistically. By inputting values for the above parameters, you'll receive detailed insights into the cost implications of utilizing customized MT solutions. This calculator lets you compare different MT approaches, assess their affordability, and make informed decisions aligned with your organization's translation needs and budget. Note that all costs are in USD. We do not store the data inserted into or produced by the calculator. Input Parameters The Calculator Understanding Machine Translation Costs Understanding MT costs is crucial for efficient resource allocation in language projects. Here's a breakdown of four typical cases as ballpark cost estimates: Generic commercial MT engine, 10 million words/year, MT management ➔ USD 2,100 annual cost Adaptive MT engine, 10 million words/year, MT management ➔ USD 6,000 annual cost MT from LLM, 10 million words/year, MT management, prompting ➔ USD 8,000 annual cost Customized MT, 10 million words/year, 2 domains, 10 languages ➔ USD 23,000 annual cost These examples highlight the varying financial implications of different MT technologies, aiding decision-makers in optimizing budgets for translation processes. Put the Calculator to Work For You! It only takes a few minutes to plug in your specific numbers related to words processed, domains, languages, and more to generate a customized cost analysis. Don't keep these important findings to yourself – we highly recommend taking a screenshot of the output page to share with your boss or clients. Seeing an accurate financial projection based on your actual translation data will help gain their support for optimizing your MT strategy. Use Win+Shift+S on Windows / CMD+Shift+S+4 on Mac to take the snapshot of your calculation. Exploring Alternatives to Customized MT Adaptive MT Adaptive MT revolutionizes machine translation with its agility and responsiveness, catering to dynamic linguistic demands. Unlike static systems, Adaptive MT swiftly adapts to evolving terminologies and styles, enhancing translation accuracy and fluency while aligning with changing business needs. Its continuous learning approach eliminates the need for frequent manual updates, streamlining workflows and boosting productivity. Furthermore, Adaptive MT empowers users with unprecedented customization options, allowing for tailored translations that effortlessly meet specific project requirements. Through real-time feedback and integration with translation memories, linguists refine translations iteratively, ensuring consistent quality and alignment with evolving needs. This collaborative process fosters a culture of continuous improvement, where users actively shape MT outputs to suit their preferences, ushering in a new era of efficient and adaptive translation solutions. Scalability through LLMs Customized NMT requires separate models for each domain and language pair, which has scaling limitations. Additional issues of the traditional customization approach are: The improvements of re-training on modern, well-established custom-trained systems are typically incremental. The training process is more cumbersome than using LLMs out-of-the-box with in-context learning and prompt engineering. The amount of effort for customized MT training is often underestimated. A large amount of language data needs to be collected, verified for relevance and quality, cleaned, and intensive training rounds perhaps with multiple iterations and evaluation checks take significant effort. Today, LLMs provide a unified framework that could more easily support on-demand translation for new language pairs and content areas than building and maintaining many specialized NMT systems. You can instruct LLMs to do certain things while producing translations. The adaptation techniques are much more flexible. The exceptions would be specialized fields like Legal or Healthcare. Making the complex simple: 5 ways of how to use MT today Currently, there are five main ways to use machine translation. Each has its benefits and disadvantages, so let’s take a high-level look at them. For a more in-depth insight, our Enterprise Automated Translations - LLM or Neural MT article is a recommended read. 1. Generic NMT engines The output quality from generic NMT engines can vary based on language pair, content type, MT engine, training data, and context. While popular engines like Google Translate, Microsoft Translator, and DeepL offer convenience, their translations may vary in accuracy and fluency. These engines utilize different algorithms and training data, impacting their performance, although features like glossaries create low-level modulation capabilities. 2. Customizable NMT engines Customizable MT systems (such as Microsoft Custom Translator or Systran) offer tailored solutions to specific domains or industries, resulting in higher-quality translations than generic MT engines. Customized MT systems can better handle specialized terminology, nuances, and context by leveraging domain-specific training data and fine-tuning algorithms. 3. Adaptive NMT engines Adaptive machine translation systems (such as LILT, ModernMT, and LanguageWeaver) dynamically adjust and improve their translation quality gradually over time—compared to the quarterly or annual retraining of customizable NMT—by learning from user feedback and corrections. These systems use advanced artificial intelligence and machine learning techniques on the fly to refine their models based on real-world usage data. Adaptive MT systems can deliver more accurate and contextually appropriate translations by adapting to users' specific preferences and language patterns. 4. LLMs MT provided by LLMs represents a cutting-edge approach to language translation, leveraging advanced neural network architectures and vast amounts of pre-training data. LLMs excel in capturing complex linguistic patterns and nuances, yet their maturity level is still evolving. Due to their requirement for specific knowledge and contextual understanding, LLM-based MT should be utilized selectively. 5. Synergized LLMs and NMTs The integration of LLMs and NMT in translation workflows is enhancing efficiency. Critical use cases enabled by LLMs—such as source optimization, machine translation quality estimation, and automatic post-editing—are becoming standard practices in innovative, integrated machine translation workflows. It should be clear that there is no one-size-fits-all machine translation solution. Careful consideration of your specific translation goals, content, and budget is required. While generic engines provide a simple starting point, customized approaches can better optimize quality outcomes at the cost of… well, cost. However, the translation landscape is constantly evolving. Hybrid methods leveraging the strengths of different technologies, like pairing LLMs with traditional MT, may unlock even greater potential. Adaptive systems also ensure your translation assets keep pace with changing needs. Most importantly, expert guidance can help you navigate this complexity to extract maximum value from your MT investment. An effective strategy considers immediate and long-term requirements to support your workflows now and in the future. Rather than viewing MT costs as expenses, see them as opportunities. Proper optimization streamlines translation processes, freeing up resources for your core business. Partners with a nuanced understanding of the latest techniques facilitate more informed choices in solutions and oversight. As a trusted partner, Nimdzi is uniquely positioned to help your organization achieve translation excellence by using machine translation's full capabilities. Our assessment services determine the optimum mixture of technologies and management practices tailored to your unique context. By working collaboratively, we ensure your MT deployment enhances global communication and supports your mission in a sustainable, scalable manner. Ultimately, the true success is how well language barriers dissolve to connect people worldwide through your essential messages and content.