Perplexity Sonar Pro
Perplexity's premium web-grounded search model with multi-step reasoning over live sources.
Perplexity Sonar Pro is text & chat AI model from Custom, priced at €3.00 per 1M input tokens with a 200K tokens context window.
0.7
Pricing
API Integration
Use our OpenAI-compatible API to integrate Perplexity Sonar Pro into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
// Simple — just pass a string
const reply = await rw.run("sonar-pro", "Hello! What can you do?");
console.log(reply);
// With message history
const reply2 = await rw.run("sonar-pro", [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Explain quantum computing simply." },
]);
console.log(reply2);
// Full response with usage info
const res = await rw.chat("sonar-pro", [
{ role: "user", content: "Hello!" },
], { temperature: 0.7, max_tokens: 500 });
console.log(res.choices[0].message.content);
console.log(res.usage);Deep dive — Perplexity AI's Perplexity Sonar Pro
Perplexity AI was founded in August 2022 by Aravind Srinivas (CEO, ex-OpenAI and DeepMind/Google Brain), Denis Yarats (CTO, ex-Meta AI), Andy Konwinski (co-founder of Databricks) and Johnny Ho. The company built an answer engine that combines live web search with LLMs to return cited answers, positioning itself as a search alternative to Google. Perplexity rapidly raised over $500M from IVP, NEA, NVIDIA, Jeff Bezos, Susan Wojcicki and others, reaching a $9B valuation in late 2024 and a higher valuation in 2025. The Sonar model family debuted in late 2024 as Perplexity's in-house RAG-tuned models, with Sonar as the fast default tier and Sonar Pro as the higher-capability variant for advanced research workloads. Sonar Pro pairs deeper search (more queries per request, more sources synthesised) with a stronger underlying LLM, available via the Perplexity API and the Perplexity Pro consumer tier. The company also partners with Apple Intelligence and several US publishers for revenue-sharing on cited content. Beyond Sonar, Perplexity ships Perplexity Pages, Spaces and Discover surfaces, and runs ad-free Pro and Enterprise subscriptions.
Visit Perplexity AI →Perplexity Sonar Pro is the high-capability tier of Perplexity's in-house Sonar family, launched alongside the Sonar API in January 2025. It is a Llama-3.x-derived large model fine-tuned by Perplexity for deep retrieval-augmented answering. Compared to base Sonar, Sonar Pro runs a more aggressive retrieval pipeline: it issues multiple parallel search queries per request, retrieves more documents (up to a few dozen sources), performs intermediate ranking and synthesis steps, and produces longer, more structured answers with denser inline citations. The underlying LLM is a larger and more capable checkpoint than base Sonar, trained with extended supervised fine-tuning on Perplexity's curated multi-hop research answers and preference optimisation against expert-rated grounding quality. Sonar Pro supports a 200K context window, structured output, and exposes additional response fields including a list of all sources visited and the search queries used. The API is OpenAI-compatible, making it a drop-in replacement for stacks that need higher answer quality and citation coverage. Pricing is roughly $5 per 1,000 search-augmented requests plus token costs, positioning it as a premium tier for research and enterprise use cases.
- Parameters
- Undisclosed (Llama-3.x-derived large)
- Context
- 200K tokens
- Deeper retrieval pipeline: multiple parallel searches and intermediate ranking
- 200K context window
- Denser inline citations and longer structured answers
- Exposes search queries and visited sources in API response
- OpenAI-compatible chat completions API
- Larger underlying LLM than base Sonar
- Suitable for multi-hop research questions
- Structured output (JSON schema) supported
- Available in Perplexity API and Perplexity Pro consumer tier
- Higher accuracy than base Sonar on long-form factual queries
- Best for: research workflows, financial and policy briefings, multi-hop fact-finding, premium chat experiences.
Built on a Llama-3.x-derived large base, fine-tuned on Perplexity's curated multi-hop research answers, expert-rated grounding preference data and synthetic deep-retrieval QA pairs. At inference time, augmented with multi-query retrieval from Perplexity's in-house search index.
License: Proprietary commercial license via the Perplexity API and Pro/Enterprise subscriptions. Weights not released.
Known limitations
- Higher cost than base Sonar
- Quality dependent on Perplexity's retrieval index
- Closed weights; no on-prem option
- Citations occasionally over-cite or mismatch the claim
- Latency higher than base Sonar due to multi-query search
Frequently asked questions
Related Models
View all Text & ChatBio_ClinicalBERT
The original Bio_ClinicalBERT from Alsentzer et al., a BERT model initialized from BioBERT and further pretrained on all MIMIC-III clinical notes. Served as a fill-mask endpoint it predicts masked tokens in clinical text and produces clinical embeddings. It is the standard encoder backbone behind many downstream clinical NLP fine-tunes.
Biomedical NER (all entities)
Token-classification model from d4data that tags 84 biomedical entity types in clinical and medical text, including disease, sign, symptom, medication, dosage, lab value, body part and procedure. Trained on the Maccrobat clinical case corpus on a DistilBERT base, so it runs cheaply for high-volume tagging.
Claude Opus 4
Anthropic's most powerful model. Exceptional at complex analysis, agentic tasks, and extended reasoning.
Claude Opus 4.8
Anthropic's most capable Opus-tier model. State of the art on long-horizon agentic work, coding and knowledge tasks, with a 1M-token context window at standard pricing.
Start using Perplexity Sonar Pro today
Get started with free credits. No credit card required. Access Perplexity Sonar Pro and 100+ other models through a single API.