Google DeepMind just opened the doors to build with three model options—Nano, Banana 2 Lite, and Gemini Omni Flash. Here’s a quick, practical guide to pick the right one and ship fast. Source: DeepMind.
What launched (and why it matters)
Different models excel under different constraints. Think in terms of latency, privacy, modality, and cost—not just raw capability.
- Shipping on-device, privacy-first features or offline UX? Start with Gemini Nano (on-device footprint, low latency).
- Designing fast, multimodal assistants or chat UIs that feel instant? Try Gemini Omni Flash (optimized for responsiveness and streaming).
- Building lightweight services or edge workloads where efficiency matters? Evaluate Banana 2 Lite (lean model profile for cost-sensitive tasks).
Quick start: 30‑minute build plan
- Define constraints: target latency (e.g., <300 ms UI updates), modalities (text, image, audio), and a per-request cost ceiling.
- Spin up the API in Google AI Studio or SDKs: Gemini API docs.
- Prototype with streaming for responsiveness; render partials and show typing indicators for better UX.
- Create a tiny eval set (25–50 examples) that mirrors your users’ inputs. Log latency, accuracy, refusal rates, and cost per call.
- Add safety guardrails early (input/output filters, PII redaction, blocklists). See safety guidance.
Implementation checklist
- Context management: keep prompts short, chunk long text, and send only relevant images or frames.
- Streaming UX: show partial tokens, progressively reveal results, and time out gracefully.
- Reliability: retries with jitter, circuit breakers, and model fallbacks (e.g., cached responses or on-device Nano when offline).
- Versioning: pin model versions and keep a changelog for reproducible evals.
- Privacy & compliance: minimize data retention, encrypt in transit, and avoid logging sensitive user content.
Prompts and patterns that work
- Concise tasking: “You are a concise assistant. Output: JSON with {answer, sources}. If unsure, say ‘unknown’.”
- Multimodal grounding: “Given this image + transcript, extract 3 bullet insights with timestamps. No speculation.”
- On-device fast path: “Classify intent as one of [navigate, call, message, search]. One word only.”
Takeaway
Pick the model by constraint: on-device privacy and speed (Nano), responsive multimodal apps (Omni Flash), or lean, cost-aware workloads (Banana 2 Lite). Start small, stream early, and measure everything.
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