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Perplexity: Sonar

来源介绍(英文)

Sonar is lightweight, affordable, fast, and simple to use — now featuring citations and the ability to customize sources. It is designed for companies seeking to integrate lightweight question-and-answer features...

模型概览

模型规格

上下文
127,072 tokens
最大输出
114,364 tokens
架构
text+image->text
分词器
Other
知识截止时间
暂未提供
内容审核
否
OPENROUTER

完整价格

同步自 OpenRouter。Token 价格均按每百万 Token 展示。

输入
$1
每百万 Token
输出
$1
每百万 Token
网页搜索
$5
每千次调用
API

快速调用

在本地设置 OPENROUTER_API_KEY。Python 需安装 requests;JavaScript 在 Node.js 中运行。密钥应保存在服务端。

API 文档

curl --fail-with-body https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"perplexity/sonar","messages":[{"role":"user","content":"Hello!"}]}'
能力与模态

输入 → 输出

输入
textimage
输出
text
API

支持的 API 参数

frequency_penaltymax_tokenspresence_penaltytemperaturetop_ktop_pweb_search_options
可用提供方

1 提供方

核验日期: 2026年9月7日

在 OpenRouter 查看实时 Provider

Provider 可用性、延迟、吞吐量和路由会持续变化,请前往来源页面查看实时运行数据。

OpenRouter

Perplexity

暂未提供
上下文
127K
最大输出
114K
输入
$1
输出
$1
缓存读取
暂未提供
缓存写入
暂未提供
perplexity

4 个模型

全部模型
perplexity logoperplexity

Perplexity: Decider Flash V1.2

Decider Flash V1.2 is a 4B-parameter decision model from Perplexity, a smaller, lower-cost sibling of Decider V1.2 with the same API contract. Instead of generating text, it reads content passed...

上下文
262K
输入
text · image
输出
decisions
输入: $0.01 每百万 Token输出: 免费 每百万 Token
查看模型详情 →
perplexity logoperplexity

Perplexity: Decider V1.2

Decider V1.2 is a new 27B checkpoint of Perplexity's decision model, succeeding Decider V1.1 27B with the same API contract. Instead of generating text, it reads content passed as state...

上下文
262K
输入
text · image
输出
decisions
输入: $0.02 每百万 Token输出: 免费 每百万 Token
查看模型详情 →
perplexity logoperplexity

Perplexity: Embed V1 4B

pplx-embed-v1 -4B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized for standard dense text retrieval with the 4B parameter model maximizing retrieval...

上下文
32K
输入
text
输出
embeddings
输入: $0.03每百万 Token
查看模型详情 →
perplexity logoperplexity

Perplexity: Embed V1 0.6B

pplx-embed-v1-0.6B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized for standard dense text retrieval with the 0.6B parameter model targeting lightweight, low-latency...

上下文
32K
输入
text
输出
embeddings
输入: $0.004每百万 Token
查看模型详情 →