Perplexity trails new Sonar Testing model with reasoning

Perplexity is currently conducting internal tests of a model labeled as Sonar Testing, which appears in the model selector with a dedicated reasoning toggle. This toggle sets it apart from the existing Sonar model, which was already recognized for its speed and navigational capabilities. In recent updates, Perplexity has also started moving toward a more unified model selector, rather than duplicating reasoning and non-reasoning variants, a toggle is introduced for models that support the additional reasoning functionality.

For end users, particularly those relying on Perplexity for fast search, summarization, and information extraction, the new Sonar Testing model is likely targeting both accuracy and versatility. By allowing users to enable or disable reasoning directly, Perplexity gives more control over how results are generated, which should benefit those who need both quick facts and more in-depth, structured answers in one place. It’s expected that this model will outperform the existing Sonar version in areas like instruction following and overall consistency, which are core feedback points from frequent users.

The model’s fast response time is preserved, with navigational results and links surfacing almost immediately. The addition of reasoning may also hint at improvements in handling more complex queries or larger context windows, another commonly requested upgrade among Perplexity’s core audience of researchers, students, and power users. The timeline for public rollout remains unclear, but given the typical pace of Perplexity’s product experiments, the upgraded Sonar model could transition from internal testing to wider release within a matter of weeks.

For context, Perplexity has established itself as a rapid innovator among AI search companies, routinely post-training its models for speed and search fluency. The Sonar line, in particular, has been positioned as the go-to for instant results and link-rich summaries, and an upgrade here would reinforce Perplexity’s strategy of keeping pace with advanced retrieval and reasoning models from larger rivals.