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OnePlus parts ways with Hasselblad as it builds its own camera engine

OnePlus confirmed it is ending its five-year camera partnership with Hasselblad and will develop an in-house DetailMax imaging engine for upcoming flagships. Oppo, by contrast, extended its Hasselblad deal and continues work on the Lumo imaging system, creating a split in how BBK-owned brands handle computational photography.

Published September 5, 2025 at 07:13 AM EDT in Software Development

What happened

OnePlus CEO Pete Lau announced that the five-year collaboration with camera maker Hasselblad has ended. Going forward, OnePlus will drop the Hasselblad badge and develop its own imaging stack, the OnePlus DetailMax Engine, for upcoming flagships — likely the OnePlus 14 (or 15 in some markets).

Hasselblad’s work with OnePlus (and BBK sibling Oppo) helped lift OnePlus camera performance over recent years by contributing to imaging algorithms, tuning, and brand credentialing. Now OnePlus says it will bring that expertise in-house rather than carry the Hasselblad logo.

Oppo’s different path

In contrast, Oppo recently extended its Hasselblad partnership and continues to promote its Lumo imaging engine introduced earlier in the year. That creates a curious split inside the BBK family: one brand internalizing imaging R&D while another doubles down on third-party collaboration.

Why this matters

Computational photography is a key differentiator in flagship phones. Whether through a branded collaboration or an in-house engine, the real value comes from data, models, tuning pipelines, and tight SoC integration. A logo on the camera can persuade buyers, but performance is built in code and datasets.

For consumers, this split means more variety in image character and possibly faster feature development from OnePlus if it truly owns the stack. For competitors, it signals that partnerships are one path but not the only one to achieve top-tier photography.

Technical implications

Building an imaging engine in-house requires significant investment across several areas:

  • Curating diverse, high-quality photo datasets for training and tuning
  • MLOps and model deployment tightly integrated with camera ISP and SoC
  • Continuous A/B testing and perceptual tuning across lighting, sensors, and lenses
  • Trade-offs between signature image style, dynamic range, and computational artifacts

Strategic choices and market impact

OnePlus moving in-house could speed feature parity with Oppo or enable a distinct photographic identity. But it also places pressure on OnePlus to deliver measurable gains — not just marketing. Oppo’s continued partnership with Hasselblad shows that co-branding still has value when paired with deep engineering input.

For industry watchers, this is a reminder that camera differentiation will come from where teams invest: data pipelines, model validation, and integration with sensors and silicon — not just a name on the module.

What organizations should consider next

Phone makers and partners should map the roadmap for imaging capabilities, decide where IP should live, and build cross-functional teams that cover data collection, on-device ML, and perceptual QA. Whether you partner with a specialist or internalize development, success depends on measurable benchmarks and tight SoC collaboration.

As OnePlus prepares its next flagship, all eyes will be on the DetailMax Engine: will it match or exceed the gains from the Hasselblad era? Expect rapid comparisons to Oppo’s Lumo-tuned devices and a fresh round of testing from reviewers and engineers alike.

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