NexAIX-官方博客
How to Choose an Open-Source LLM API: Pitfalls to Avoid from Self-Hosted Clusters to Low-Cost Resale and Production-Grade Hybrid Calls
As trillion-parameter open-weight MoE models catch up with frontier closed-source models in coding and agent scenarios, more teams are shifting daily traffic to open-source LLM APIs. This article breaks down the hidden barriers of self-hosted GPU inference, analyzes the risks of second-hand quota resale and hidden downgrades, and provides a production-grade selection checklist based on proprietary compute deployment, zero logging, and single-endpoint hybrid calls.
How to Verify Whether an AI API Logs Your Conversations: What You Can Check, What You Can't, and How to Prevent It
Client-side checks alone cannot prove a server doesn't log conversations; this article explains which checks provide useful evidence—auditing console log fields, reading data retention policies, using canary tokens to detect leaks, inspecting your own pipeline, and sanitizing data before it leaves your boundary.
How to Verify a Zero-Log AI API? A Four-Category Data Retention Checklist
A practical guide to verifying zero-log AI APIs: four data categories with different verifiability, plus a pre-contract checklist for field-level written commitments.
