Open-Source Model Stack 2026

The open-weight model landscape in 2026 has reached genuine enterprise viability. Llama 4 Scout (109B active parameters, 17B MoE), Qwen3 235B-A22B, Mistral Small 4 (22B), and DeepSeek V3-0324 are not research artifacts; they are built for production systems that enterprises are deploying in regulated, latency-sensitive, and air-gapped environments where closed API models cannot be used.

The problem is that choosing between them requires navigating a complex space of license terms, inference cost profiles, fine-tuning behavior, language coverage, and compliance implications. A model that is optimal for a Taiwanese financial institution's document processing workflow is not the same model that is optimal for a Japanese hospital's clinical summarization use case.

This whitepaper presents the decision framework Tenten AI has developed across 20+ enterprise open-weight model deployments in 2025–2026. Rather than repeat one of the many benchmark comparisons, it focuses on the practical model-selection lessons that surface only after deploying these models and observing where each succeeds and fails.