Looking to optimize LLM costs and latency whilst maintaining output quality? Look no further than model distillation.

Model distillation is the process of tuning a smaller LLM on outputs from a larger one. As a result of distillation, the smaller LLM acquires the reasoning patterns of the larger at specified trained tasks while requiring a fraction of the compute and memory. The end result is lower token costs and lower latency/faster response, all at a fine-tuned and validated high level of performance.

OptimumPartner AI is an end-to-end fine tuning data company which specialises in model distillation and fine-tuning services, serving English speaking markets across North America and Europe.

1. We engage with you via call to gain a scope of what your project/app requirements are.
2. We create a dataset of outputs from a larger more performant model.
3. We distill the larger model outputs into a smaller model via fine-tuning.
4. We create a ‘validation’ data set and test the new model’s performance against it.
5. We iterate on the original large model dataset and feed it into a new fine tune program until performance level is reached with the smaller model.
6. The result: large model performance for specified tasks at a fraction of the compute cost and latency.