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Documentation Index

Fetch the complete documentation index at: https://docs.kymaapi.com/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

sonar is Perplexity’s live web-search model. Instead of answering from training data alone, it runs a real-time search of the web on every request and returns a current answer with citations. Reach for it when the answer depends on fresh information — news, prices, scores, releases, schedules, or docs that change after a model’s training cutoff. Sonar does its own searching internally. You send a question; it returns a grounded, cited answer. There is no tool-calling step for you to wire up — and no tool-calling support if you wanted one (see below).

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Specs

FieldValue
Model IDsonar
Best forLive web search, current events, research with citations
Context window127K
Max output tokens4K
Input modalitiesText, image
Output modalitiesText
Tool callingNo
Structured outputsNo
Prompt cachingNo
SpeedMedium
Cost bandBalanced
Release stageStable

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Pricing

Sonar bills two ways on the same request:
  • Tokens — 1.35/1Minput,1.35 / 1M input, 1.35 / 1M output, just like any chat model.
  • Web-search fee — a flat $0.00675 per request, on top of tokens, because every call performs a live search.
Short questions are dominated by the search fee, not the tokens. Every response’s usage.cost already includes the search fee. See Pricing → Web search for the full explanation.

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Use this when

  • The answer depends on current information — news, prices, releases, schedules, live status.
  • You want sources: Sonar returns citations alongside the answer.
  • You want web grounding without building your own search + scrape + RAG pipeline.

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Pick something else when

  • You need deeper, multi-step research or longer cited reports: use sonar-pro.
  • You need function calling / tools: Sonar has none — use kimi-k2.6 or qwen-3.6-plus.
  • The task does not need fresh web data: a standard model is cheaper, with no per-request search fee.

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Example

from openai import OpenAI

client = OpenAI(base_url="https://kymaapi.com/v1", api_key="ky-...")

response = client.chat.completions.create(
    model="sonar",  # or the alias "search"
    messages=[{"role": "user", "content": "What shipped in the latest Bun release, and when?"}]
)

print(response.choices[0].message.content)
AliasResolves to
searchsonar