A top-tier closed model such as GPT-5.5, Claude Sonnet 4.6, or Grok-3 is usually the best quality baseline. GPT-5.5 now includes video understanding and live web access. Then add lower-cost models such as Gemini 3.5 Flash, Gemma 4, or Llama 4 Scout (25% faster) for bulk throughput.
Yes, when you need strong data control, predictable cost at scale, or low-latency regional deployment. Gemma 4, Llama 4 Maverick (now with visual reasoning), Ministral 3 8B, and newer DeepSeek models are now common short-list candidates for this path.
Start with one primary (GPT-5.5, Claude Sonnet 4.6, or Grok-3) and one fallback model (e.g., Gemini Flash). Add a third open model tier (for example Gemma 4 or Llama 4 Maverick) only when your evals prove measurable gains over two-tier routing.
No. Most mature systems use model specialization by task, latency target, and quality requirements.