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Evaluate your model performance
Match evaluation frameworks to intended outcomes, gain actionable insights on your model’s strengths and weaknesses, and improve performance with comprehensive evaluation and analysis.
Leading LLM companies and research organizations have trusted Turing
Rigorous investigation, real insights
Comprehensive evaluation of large language models is key for unlocking its full potential and ROI.
Turing tailors proven methodologies and benchmarking frameworks to accurately assess effectiveness, reliability, and scalability across various business applications—ensuring your LLM performs at the highest standards.
Turn evaluation insights into real performance gains.
A comprehensive analysis approach
Use Turing’s expertise in training the highest-quality foundation models to thoroughly evaluate your LLM’s capabilities.
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Deep model evaluation
Objectively assess model performance using our optimized exploration algorithms coordinating human focus areas.
Benchmark performance analysis
Deep dive into when and why your model achieves specific scores on comparative, custom, or industry-standard benchmarks.
Human-in-the-loop testing
Integrate human feedback to research and compile community findings from diverse data sources for a structured evaluation of already-deployed models.
Model evaluation capabilities
Ensure your LLM excels in performance, accuracy, and reliability with several evaluation capabilities. With our expert guidance, your model will meet the highest standards and deliver exceptional results in real-world applications.
Accuracy and precision testing
Efficiency and scalability assessment
Robustness and reliability analysis
Performance benchmarking
User interaction and usability testing
Compliance and security auditing
Comprehensive model evaluation and evolution starts here
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Model assessment and strategy
Our in-house solution architects and experts perform a curated evaluation and analysis, then provide you with a recommended path to enhanced performance and more.
Fully-managed large language model training
Using our vetted technical professionals, we build your fully managed team of model trainers and more—with additional customized vetting, if necessary.
LLM data and training tasking
You focus solely on task design while we handle coordination and operation of your dedicated training team.
Scale on demand
Maintain consistent quality control with iterative workflow adaptation and agility as your training needs change.
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Get continuous improvement and performance. Talk to one of our solution architects today.
Cost-efficient R&D for LLM training and development
Empower your research teams without sacrificing your budget or business goals. Get our starter guide on strategic use, development of minimum viable models, and prompt engineering for a variety of applications.
“Turing’s ability to rapidly scale up global technical talent to help produce the training data for our LLMs has been impressive. Their operational expertise allowed us to see consistent model improvement, even with all of the bespoke data collection needs we have.”
How does your model measure?
Talk to one of our solution architects and start your large language model performance evaluation.
Frequently asked questions
Find answers to common questions about training and enhancing high-quality LLMs.
What does Turing's LLM evaluation process look like?
Our large language model evaluation services are comprehensive and tailored to your model's specific outcomes. It includes deep model evaluation using optimized exploration algorithms, benchmark performance analysis against industry standards, and human-in-the-loop testing to integrate research and community findings. Our approach ensures a precise assessment of your model’s performance, providing actionable insights into its strengths and weaknesses.
How does Turing ensure real world performance and accuracy in LLM models?
We ensure high performance and accuracy through rigorous testing of model outputs using benchmark datasets and real-world scenarios. This includes accuracy and precision testing across various tasks, performance benchmarking, usability testing, and compliance and security auditing to evaluate model responses for their effectiveness, reliability, and scalability in real business applications.
What is human-in-the-loop testing, and why is it important?
Human-in-the-loop testing involves integrating human feedback into the evaluation process, allowing a structured large language model assessment of already-deployed models based on real user interactions and community findings from diverse data sources. It helps identify and address practical issues that automated tests might miss, ensuring the model performs effectively in real-world applications.
How does Turing address efficiency and scalability issues in LLM models?
We address efficiency and scalability issues by evaluating your LLM’s processing speed, resource usage, and scalability under increasing data sizes and usage demands. This includes stress-testing with edge cases and adversarial examples to guarantee robust performance.
How does Turing handle compliance and security during LLM evaluation?
We handle compliance and security by auditing the model’s data handling, privacy measures, and security protocols. This ensures your LLM adheres to industry regulations and security best practices, protecting sensitive information and maintaining compliance with legal standards. This process includes thorough evaluations to safeguard against potential vulnerabilities.
Does Turing use proprietary evaluation tools?
Yes, we use proprietary evaluation tools optimized for comprehensive LLM assessment. Our tools coordinate human focus areas with automated exploration algorithms, providing deep insights into model performance. These tools offer precise and actionable recommendations to enhance your LLM's capabilities and ensure it meets the highest standards.