Meta: Llama 3.2 1B Instruct

Meta's Llama 3.2 1B Instruct model consistently ranks among the fastest models and offers highly competitive pricing across all evaluated benchmarks. This 1-billion-parameter model, designed for efficiency in low-resource environments, demonstrates its cost-effectiveness particularly well. While excelling in cost and speed, its accuracy performance varies significantly across categories. It achieved a notable 32.0% accuracy in Email Classification, placing it in the 6th percentile for accuracy but impressively within the top 3 for cost and 93rd percentile for duration, indicating strong efficiency for this task. Similarly, in Reasoning, it showed a 28.6% accuracy (16th percentile) but again secured a top 3 position for cost and the best accuracy-to-cost ratio. However, the model exhibited very low accuracy in Instruction Following (18.9%), and zero accuracy in Coding, Ethics, and General Knowledge, suggesting significant limitations in these complex domains. Its strengths lie in its operational efficiency and cost-effectiveness, making it suitable for tasks where these factors are paramount, especially in classification and basic reasoning, but less so for tasks requiring deep knowledge or complex problem-solving.