ModelScout SDK Just Launched — Here's How to Benchmark 56+ AI Models via NexaAPI

ModelScout just dropped a Python SDK for LLM benchmarking. I combined it with NexaAPI (the cheapest inference API at $0.003/call) to run 1000 benchmark evaluations for just $3. What Is ModelScout SDK? ModelScout benchmarks LLMs side-by-side on your data — quality scores, cost analysis, latency metrics. pip install modelscout-sdk nexaapi Why NexaAPI for Benchmarking? Running 1000 eval calls costs: NexaAPI : ~$3 (at $0.003/call) OpenAI direct: $15-50 Other APIs: $10-30 NexaAPI saves 70-90% — perfect for large-scale benchmarking. Get your free API key (100 free calls): rapidapi.com/user/nexaquency Python Example from nexaapi import NexaAPI client = NexaAPI ( api_key = ' YOUR_NEXAAPI_KEY ' ) def run_benchmark_prompt ( prompt : str , model : str = ' gpt-4o ' ) -> str : """ Use NexaAPI as inference backend for ModelScout evaluations """ response = client . chat . completions . create ( model = model , messages = [{ ' role ' : ' user ' , ' content ' : prompt }] ) return response . choices [ 0