Unlock exclusive introductory pricing for the newly launched Gemini 3.5 Flash.
Q

qwen3.5-plus

Entrada:$0.32/M
Saída:$1.92/M
Lançado:Feb 16, 2026

The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency.

Novo
Uso comercial

Playground para qwen3.5-plus

Explore o Playground do qwen3.5-plus — um ambiente interativo para testar modelos e executar consultas em tempo real. Experimente prompts, ajuste parâmetros e itere instantaneamente para acelerar o desenvolvimento e validar casos de uso.

Technical Specifications of Qwen3.5‑Plus

ItemQwen3.5‑Plus (hosted API specs)
Model familyQwen3.5 (Alibaba Tongyi Qianwen)
ArchitectureLarge‑scale MoE foundation with multimodal extensions
Input typesText, Image (vision)
Output typesText (reasoning, code, analysis)
Context windowUp to 1,000,000 tokens (Plus / hosted tier)
Max output tokensProvider‑dependent (long‑form supported)
Reasoning modesFast / Thinking (deep reasoning)
Tool useBuilt‑in search, code interpreter, agent workflows
Languages200+ languages
DeploymentHosted API (OpenAI‑compatible format)

What is Qwen3.5‑Plus

Qwen3.5‑Plus is the production‑grade, hosted API variant of Alibaba’s Qwen3.5 foundation model family. It is built on the same large‑scale architecture as the open‑weight Qwen3.5‑397B model, but extends it with significantly larger context capacity, adaptive reasoning modes, and integrated tool usage designed for real‑world applications.

Unlike the base open model (which typically supports up to 256K tokens), Qwen3.5‑Plus is optimized for ultra‑long‑context reasoning, autonomous agent workflows, and enterprise‑scale document and code analysis.

Main Features of Qwen3.5‑Plus

  • Ultra‑long context understanding: Supports up to 1 million tokens, enabling analysis of entire codebases, large legal corpora, or multi‑day conversation logs in a single session.
  • Adaptive reasoning modes: Developers can choose fast response generation or deeper “thinking” modes for complex multi‑step reasoning and planning.
  • Integrated tool use: Native support for search and code interpreter tools allows the model to augment reasoning with external data and executable logic.
  • Multimodal capabilities: Accepts both text and image inputs, enabling document + visual reasoning, diagram interpretation, and multimodal analysis workflows.
  • Multilingual coverage: Designed for global usage, with strong performance across more than 200 languages.
  • API‑ready for production: Delivered as a hosted service with OpenAI‑compatible request/response formats, reducing integration friction.

Benchmark Performance of Qwen3.5‑Plus

Public reporting from Alibaba and independent evaluations indicate that Qwen3.5‑Plus achieves competitive or superior results compared with other frontier‑class models on a range of reasoning, multilingual, and long‑context benchmarks.

Key positioning highlights:

  • Strong long‑document reasoning accuracy due to extended context handling
  • Competitive performance on reasoning and knowledge benchmarks relative to leading proprietary models
  • Favorable cost‑to‑performance ratio for large‑scale inference workloads

Note: Exact benchmark scores vary by evaluation protocol and are periodically updated by the provider.

Qwen3.5‑Plus vs Other Frontier Models

ModelContext WindowStrengthsTypical Trade‑offs
Qwen3.5‑Plus1M tokensLong‑context reasoning, agent workflows, cost efficiencyRequires careful token management
Gemini 3 Pro~1M tokensStrong multimodal reasoningHigher cost in some regions
GPT‑5.2 Pro~400K tokensPeak reasoning accuracySmaller context window

Qwen3.5‑Plus is particularly attractive when context length and agent‑style workflows matter more than marginal gains in short‑context accuracy.

Known Limitations

  • Token management complexity: Extremely long contexts can increase latency and cost if prompts are not carefully structured.
  • Hosted‑only features: Some capabilities (e.g., 1M token context, integrated tools) are not available in open‑weight variants.
  • Benchmark transparency: As with many hosted frontier models, detailed benchmark breakdowns may be limited or updated over time.

Representative Use Cases

  1. Enterprise document intelligence — analyze contracts, compliance archives, or research corpora end‑to‑end.
  2. Large‑scale code understanding — reason across monorepos, dependency graphs, and long issue histories.
  3. Autonomous agents — combine reasoning, tool usage, and memory for multi‑step workflows.
  4. Multilingual customer intelligence — process and reason over global, multilingual datasets.
  5. Search‑augmented analysis — integrate retrieval and reasoning for up‑to‑date insights.

How to Access Qwen3.5‑Plus via API

Qwen3.5‑Plus is accessed through hosted APIs provided by CometAPI and compatible gateways. The API generally follows OpenAI‑style request formats, enabling straightforward integration with existing SDKs and agent frameworks.

Developers should select Qwen3.5‑Plus when their applications require very long context, multimodal reasoning, and production‑ready tool orchestration.

Step 1: Sign Up for API Key

Log in to cometapi.com. If you are not our user yet, please register first. Sign into your CometAPI console. Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.

Step 2: Send Requests to qwen3.5-plus pro API

Select the “qwen3.5-plus” endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. Replace <YOUR_API_KEY> with your actual CometAPI key from your account. Where to call it: Chat format.

Insert your question or request into the content field—this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

FAQ

Preços para qwen3.5-plus

Explore preços competitivos para qwen3.5-plus, projetado para atender diversos orçamentos e necessidades de uso. Nossos planos flexíveis garantem que você pague apenas pelo que usar, facilitando o dimensionamento conforme suas necessidades crescem. Descubra como qwen3.5-plus pode aprimorar seus projetos mantendo os custos gerenciáveis.

ModelComet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
qwen3.5-plus
Entrada:$0.32/M
Saída:$1.92/M
Entrada:$0.4/M
Saída:$2.4/M
-20%
qwen3.5-plus-2026-02-15
Entrada:$0.32/M
Saída:$1.92/M
Entrada:$0.4/M
Saída:$2.4/M
-20%

Código de exemplo e API para qwen3.5-plus

Acesse código de exemplo abrangente e recursos de API para qwen3.5-plus para otimizar seu processo de integração. Nossa documentação detalhada fornece orientação passo a passo, ajudando você a aproveitar todo o potencial do qwen3.5-plus em seus projetos.

#!/bin/bash

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

curl https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "qwen3.5-plus-2026-02-15",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }'

cURL Code Example

#!/bin/bash

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

curl https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "qwen3.5-plus-2026-02-15",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }'

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)

completion = client.chat.completions.create(
    model="qwen3.5-plus-2026-02-15",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"},
    ],
)

print(completion.choices[0].message.content)

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const api_key = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const base_url = "https://api.cometapi.com/v1";

const openai = new OpenAI({
  apiKey: api_key,
  baseURL: base_url,
});

const completion = await openai.chat.completions.create({
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Hello!" }
  ],
  model: "qwen3.5-plus-2026-02-15",
});

console.log(completion.choices[0].message.content);

Versões do qwen3.5-plus

O motivo pelo qual qwen3.5-plus possui múltiplas versões instantâneas pode incluir fatores como variações na saída após atualizações que exigem versões antigas para consistência, fornecendo aos desenvolvedores um período de transição para adaptação e migração, e diferentes versões correspondentes a endpoints globais ou regionais para otimizar a experiência do usuário. Para diferenças detalhadas entre versões, consulte a documentação oficial.

VersionDescriptionAccess
qwen3.5-plusGeneral Version✅
qwen3.5-plus-2026-02-152026-02-15 Standard version✅
qwen3.5-plus-thinkingThinking Variations✅