Modern GenAI Landscape
GPT-5, Claude Sonnet 5 / Opus 4.7, Gemini 2.5 / Gemini 3, Llama 4 (Maverick / Scout / Behemoth), DeepSeek-V3.1 / R2, Qwen 3, Kimi K2, FLUX.1 Pro, Stable Diffusion 3.5, Midjourney v7, Sora, Veo 3, Suno v4, ElevenLabs v3, Luma Dream Machine, HunyuanVideo, Wan 2.2 — the 2025-2026 model zoo is dizzying. The skill isn't memorizing releases; it's mastering a six-axis rubric (task, quality, cost, control, latency, license) that lets you pick the right tool faster than the field can ship new ones.
Learning Objectives
After this lesson, you will be able to:
- Map every major generative-AI product in 2026 across image, video, audio, music, voice, and 3D — and know which company makes each, what it costs, and what it is best at
- Pick the right model for a job using a six-axis rubric: task fit, quality tier, cost-per-output, control (open weights vs API), latency, and license terms
- Decide when to use a hosted API (OpenAI, Anthropic, fal.ai, Replicate) versus self-host an open-weights model on your own H100 or 4090 — based on volume, latency, and customization needs
- Spot the 2025–2026 architecture convergence: diffusion transformers + flow matching for video, MoE for text, multimodal foundation models, and what comes next
Prerequisites