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 production-grade 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. It is not a benchmark comparison — there are dozens of those. It is the practical reasoning about model selection that only surfaces when you have deployed all of these models in production environments and observed where each one succeeds and fails.