Qwen3.7 Plus

by Qwen

qwen/qwen3.7-plus
Input
$0.45/1M tokens
Output
$1.79/1M tokens
Context
1Mtokens
Max output
131Ktokens
Knows to
-
Released
3 Jun 2026

About

Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series.

Pricing

Input$0.45per 1M prompt tokens
Output$1.79per 1M generated tokens, reasoning included
Cached input$0.09per 1M tokens read back from the prompt cache
Cache write$0.56per 1M tokens written to the prompt cache
Input over 256K$1.34the whole prompt is billed at this rate once it passes the threshold
Output over 256K$5.38applies to replies to those prompts

What a request costs

Typical requestEachPer 1,000
Short chat reply1,500 in · 400 out$0.0014$1.39
Question over a long document40,000 in · 800 out$0.019$19.35
Agent tool step20,000 in · 1,200 out$0.011$11.11
Very long prompt (over 256K)320,000 in · 1,500 out$0.438$438.14

At the developer-API rate, before any provider promotion or prompt-cache saving. In the app, the model picker shows what a message costs on your plan before you send it.

Benchmarks

Intelligence25.2#110 of 285
Coding55.9#73 of 163
Agentic17.5#71 of 127

Head-to-head rankings

  1. #23SVGModel arenaElo 120847% wins
  2. #24Data vizModel arenaElo 127651% wins
  3. #28WebsitesModel arenaElo 127251% wins
  4. #29CodeModel arenaElo 127150% wins
  5. #32Game devModel arenaElo 126449% wins
  6. #35UI componentsModel arenaElo 126149% wins
  7. #373DModel arenaElo 123948% wins
  8. #46ASCII artModel arenaElo 114441% wins

Scores from Artificial Analysis; bars are scaled to the best model on our list. Rankings from Design Arena head-to-head votes. Published by OpenRouter alongside its catalogue.

Call it from code

OpenAI-compatible: point any OpenAI SDK at https://api.privateer.pro/v1 and set model. Keys are created in the app under Settings.

cURL
curl https://api.privateer.pro/v1/chat/completions \
  -H "Authorization: Bearer $PRIVATEER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.7-plus",
    "messages": [{ "role": "user", "content": "Hello" }]
  }'
Python
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.privateer.pro/v1",
    api_key=os.environ["PRIVATEER_API_KEY"],
)
reply = client.chat.completions.create(
    model="qwen/qwen3.7-plus",
    messages=[{"role": "user", "content": "Hello"}],
)
print(reply.choices[0].message.content)
JavaScript
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.privateer.pro/v1",
  apiKey: process.env.PRIVATEER_API_KEY,
});
const reply = await client.chat.completions.create({
  model: "qwen/qwen3.7-plus",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(reply.choices[0].message.content);

Parameters this model accepts

frequency_penaltyinclude_reasoninglogprobsmax_tokenspresence_penaltyreasoningresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p

API reference → · How API billing works →

Prices are USD at the developer-API rate, as of 16 Oct 2026, rebuilt daily from the providers’ live catalogues. ← All models