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content/20.results.md

@@ -71,7 +71,7 @@ To achieve this goal, we implemented an encrypted pipeline that contains the ben
 
 Current results confirm the prevailing opinion of OpenAI's leading role in LLM performance (Figure @fig:benchmark A).
 Since the benchmark datasets were created to specifically cover functions relevant in BioChatter's application domain, the benchmark results are primarily a measure for the LLMs' usefulness in our applications.
-OpenAI's GPT models (gpt-4 and gpt-3.5-turbo) lead by some margin on overall performance and consistency, but several open-source models reach high performance in specific tasks (Sup Figure).
+OpenAI's GPT models (gpt-4 and gpt-3.5-turbo) lead by some margin on overall performance and consistency, but several open-source models reach high performance in specific tasks.
 Of note, performance in open-source models appears to depend on their quantisation level, i.e., the bit precision used to represent the model's parameters.
 For models that offer quantisation options, 4- and 5-bit models perform best, while 2- and 8-bit models appear to perform worse (Figure @fig:benchmark A).