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Perplexity AI: Perplexity plans and status

Perplexity AI sells an answer engine: a search box that replies in prose with links to what it read. It is the only company here whose product is a way of using models rather than a model, which is why this site tracks its consumer plan but prices no Perplexity API. Its status page has no machine readable feed, so its reading here is unknown rather than borrowed.

By Kawsar. Written . Read from Perplexity's own site, and Perplexity Pro, .

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Perplexity AI Researchers Detail LoRA Recipe For Converting Four Language Models To Diffusion

Editorial diagram showing perplexity ai researchers detail lora recipe for converting four language models to diffusion
For teams weighing whether to adopt diffusion generation, a recipe that touches only a small adapter rather than retraining a whole model changes the calculation from a multi-week pretraining budget to a few hours on one rented GPU, which...

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Diagram drawn for this item: Perplexity AI Researchers Detail LoRA Recipe For Converting Four Language Models To Diffusion. On October 30, 2026, researchers published a paper on arXiv titled BYOD: Build Your Own DLM, describing a parameter-efficient recipe that converts four autoregressive language models, Gemma 2 9B, Llama 3.1 8B, Qwen2.5 7B and Ministral 8B... For teams weighing whether to adopt diffusion generation, a recipe that touches only a small adapter rather than retraining a whole model changes the calculation from a multi-week pretraining budget to a few hours on one rented GPU, which...

A paper associated with Perplexity AI describes BYOD, a LoRA-only method that converts standard autoregressive language models into diffusion language models without full retraining.

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  1. Paper Proposes Message-Passing Method For Compressing LLM Weights

  2. Researchers Publish S-SALAAD Framework For Sparse Large Model Inference

  3. Paper Proposes Meaning-Level Reward To Go Beyond Next-Token Prediction

  4. Paper Shows Perplexity Metric Hides KV-Cache Quality Losses

  5. Stanford Team Publishes Next-Concept Modeling Paper on Faster Text Generation

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