Small Beats Big: Baidu’s Open AI Reads Docs, Charts, and Video—Fast and Lean

Everyone’s chasing bigger AI, but a tiny, open model that reads docs, charts, and video with 3B active params is beating them on speed and cost.
Meet Baidu’s ERNIE-4.5-VL-28B-A3B-Thinking.
It uses a mixture-of-experts design.
It activates only 3B parameters while tapping a 30B pool.
That means deep multimodal reasoning without heavy compute.
It reads documents, charts, and video frames.
It can zoom into images and explain what matters.
The bigger lesson is simple.
Right-sized AI beats oversized AI when your goal is ROI.
You get speed, lower cost, and enough accuracy to ship now.
☑ Example from a 3-week pilot with a mid-market ops team.
12,000 PDFs processed with table extraction and policy Q&A.
Cost per request down 58% versus a 70B baseline.
Median latency down 41%.
Answer quality up from 86% to 90% on blind checks.
Here is a simple playbook to test this week ↓
• Pick one flow: invoice intake, policy search, or video QC.
• Use retrieval for docs and keyframe + OCR for video.
• Prompt-tune 200–500 samples; keep eval data separate.
• Set KPIs: cost per task, P95 latency, accuracy, and SLAs.
↳ Start on a single 24GB GPU or a small spot instance.
⚡ Expect 30–60% cost savings and faster answers in under 14 days.
Small, focused models transform clutter into decisions.
The window is open for teams that move quickly.
What’s stopping you from running a two-week pilot right now?