These Smart Glasses Are Similar Meta Ray-Bans, but Support Google’s Gemini

Why It Matters

Embedding multiple LLMs gives Rokid a competitive edge in the fast‑growing AR wearables market, challenging incumbents like Meta and expanding Google’s ecosystem beyond smartphones.

Key Takeaways

• Rokid glasses now run Google Gemini natively.
• Supports four LLMs: Gemini, ChatGPT, DeepSeek, Qwen.
• Priced $299, 12‑hour battery, 38.5 g weight.
• Competes directly with Meta Ray‑Ban smart glasses.
• Update lets users switch AI assistants on device.

Pulse Analysis

The AR smart‑glasses segment is rapidly maturing, with Meta’s Ray‑Ban collaboration setting a high‑visibility benchmark for consumer‑grade wearables. Rokid’s “Style” model enters the arena offering comparable hardware—open‑ear audio, a 12‑megapixel camera, and a lightweight frame—while undercutting Meta on battery endurance and price. By positioning itself as a cost‑effective alternative, Rokid aims to capture early adopters who seek a seamless blend of fashion and function without the premium price tag.

What distinguishes Rokid’s latest update is the native integration of four leading large‑language models, headlined by Google’s Gemini. This multi‑assistant architecture lets users toggle between Gemini, OpenAI’s ChatGPT, DeepSeek, and Alibaba’s Qwen directly on the glasses, bypassing the need for a tethered smartphone. The move signals a broader industry shift toward on‑device AI, reducing latency and enhancing privacy while delivering richer contextual interactions in real time. For Google, embedding Gemini in a non‑Google hardware ecosystem expands its reach and data pipeline beyond traditional platforms.

From a business perspective, the $299 price point and 12‑hour battery life position Rokid to appeal to both enterprise pilots and consumer enthusiasts. The ability to switch AI assistants could drive developer interest, fostering a marketplace of voice‑first applications tailored to AR contexts. As competitors scramble to embed AI deeper into wearables, Rokid’s strategy may accelerate adoption of AI‑driven eyewear, prompting further investment in sensor miniaturization, battery efficiency, and cross‑platform AI services.