Paper Proposes Meaning-Level Reward To Go Beyond Next-Token Prediction
A new arXiv paper proposes training language models to reward meaning rather than exact wording, a shift relevant to answer engines like Perplexity.
Perplexity AI · Product data
Perplexity price, plans and limits (November 2026)
Operational
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Everything this site holds about Perplexity, on one page: whether it is working, what it costs, what its API charges, and what has changed. Every figure below was read from Perplexity AI's own pages, and every block says when. Where Perplexity AI publishes nothing, this page says so instead of estimating.
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Is Perplexity working right now?
Operationalread
Perplexity AI describes it as: All Systems Operational
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Ninety days, one cell a day
Source: status.perplexity.comRead Single sourceHistory
What Perplexity costs
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API prices
No API price list is tracked here for Perplexity AI. The vendors this site prices are listed on the API pricing page, and every vendor we price has a company page of its own under Companies.
What changed at Perplexity
Every change we have logged at Perplexity, newest first, each with Perplexity AI's own page as the receipt.
Stanford Team Publishes Next-Concept Modeling Paper on Faster Text Generation
Researchers tied to Perplexity AI's orbit published a paper describing Next-Concept Modeling, a coarse-to-fine method that generates text far faster than diffusion language models.
Study Finds Tiny Chinese BERT Models Favor MLM Over MacBERT
A paper measures candidate masking strategies by their Perplexity score, among other metrics, and finds the winner flips entirely once a Chinese BERT model shrinks to under nine million parameters.
OncoNoteBERT Encoder Trained From Scratch On UK Oncology Notes
A UK research team built OncoNoteBERT for oncology notes, a reminder that general tools like Perplexity's answer engine are not tuned for clinical text.
Perplexity AI Researchers Publish Jacobian-Lens Method For Model Pruning
Researchers at Perplexity AI published a paper describing J-BI, a Jacobian-Lens weighting method that raises depth-pruning accuracy for large language models.
Paper Edits Attention With B-Spline Surfaces To Steer Model Output
A new paper describes attention manifolds, a technique that edits how transformer models route information, with relevance for answer engines like Perplexity.
New Framework Tests Whether LLMs Truly Understand Context
A new knowledge graph based evaluation framework tests whether large language models genuinely understand context, a question that bears directly on answer engines such as Perplexity.
Paper Proposes Quality-Gated Swap of Attention Layers in Small Language Models
A new paper indexed alongside Perplexity AI's research tracking replaces some attention layers in small language models only when accuracy checks pass.
LayerRoute paper shows layer-skipping router matches wallclock speedup across ten training seeds
A single-author arXiv paper tests layer-skipping for efficient inference, the kind of cost problem answer engines like Perplexity AI's face at scale.
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