Imagination reveals powerful graphics chips for smartphones and wearables
The graphics in digital gadgets, from wearables to smart TVs, are about to get more snappy and responsive. — Imagination Technologies is launching its latest graphics cores that can be licensed by chip vendors to build full graphics chips.
Context & Ripple Effects
Imagination Technologies' launch of licensable graphics cores for smartphones and wearables sits inside a decade-long race to deliver more visual performance per milliwatt. Earlier the same year, Intel was researching ways to cut graphics power draw, signaling how central efficiency had become to mobile silicon. The licensing model Imagination uses — selling IP cores that chip vendors integrate rather than shipping its own chips — put it upstream of every smartphone and wearable GPU decision of the era.
First-order effects
- Chip vendors building phone, wearable, and smart-TV silicon can now license more capable GPU cores directly, shortening their design cycles for snappier, more responsive devices.
- Imagination strengthens its position as a merchant GPU IP supplier, competing for socket wins against rivals like ARM's Mali line at the moment wearables emerge as a new category.
Second-order effects
- Rival IP vendors are pushed to match the performance-per-watt gains, accelerating the cadence of mobile GPU generations — a race still visible years later in ARM's flagship Immortalis-G715 with hardware ray tracing and Qualcomm's Snapdragon 8 Gen 3 GPU claims.
- Device makers gain headroom to add richer UIs, gaming, and eventually on-device AI workloads to constrained wearables, pulling adjacent suppliers of displays and sensors upmarket.
Third-order effects
- If the pattern holds, graphics IP becomes a structural battleground where a handful of licensors (Imagination, ARM, and integrated players like Qualcomm) gatekeep what consumer devices can render — and where dependence on licensed IP exposes chipmakers to licensing disputes, as Imagination's later conflict with Apple over rights illustrates.
- The efficiency-first approach pioneered here foreshadows today's heterogeneous, workload-specific silicon, where GPUs share dies with NPUs and VPUs tuned for edge AI rather than general-purpose compute alone.
The trend: Mobile graphics is evolving from a raw-performance arms race into an efficiency-driven IP licensing market where specialized cores for phones, wearables, and edge AI define competitive advantage.