--- title: Qwen3.5 Plus — Multimodal LLM | ModelsLab description: Access Qwen: Qwen3.5 Plus 2026-02-15 API for 1M token context, vision-language tasks, and fast inference. Generate advanced responses now. url: https://modelslab-frontend-v2-927501783998.us-east4.run.app/qwen-qwen35-plus-2026-02-15 canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/qwen-qwen35-plus-2026-02-15 type: website component: Seo/ModelPage generated_at: 2026-05-13T10:55:39.066772Z --- Available now on ModelsLab · Language Model Qwen: Qwen3.5 Plus 2026-02-15 Multimodal Power, Million Tokens --- [Try Qwen: Qwen3.5 Plus 2026-02-15](/models/open_router/qwen-qwen3.5-plus-02-15) [API Documentation](https://docs.modelslab.com) Run Qwen3.5 Plus Efficiently --- 1M Context ### Process Massive Inputs Handle 1,000,000 tokens with text, image, video inputs via Qwen: Qwen3.5 Plus 2026-02-15 API. Hybrid Architecture ### Linear Attention MoE Qwen qwen3 5 plus 2026 02 15 uses sparse experts for 19x faster long-context decoding. Auto Reasoning ### Adaptive Tool Use Qwen: Qwen3.5 Plus 2026-02-15 LLM auto-activates search, code interpreter in Auto mode. Examples See what Qwen: Qwen3.5 Plus 2026-02-15 can create --- Copy any prompt below and try it yourself in the [playground](/models/open_router/qwen-qwen3.5-plus-02-15). Code Review “Review this Python function for efficiency and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2)” Math Proof “Prove that the sum of the first n natural numbers is n(n+1)/2 using mathematical induction. Show all steps clearly.” JSON Schema “Generate a JSON schema for a user profile including name, email, age, and preferences array with validation rules.” Logic Puzzle “Three houses in a row, owned by Alice, Bob, Carl. Alice has a dog, Bob drinks tea, Carl lives in the middle. Dog owner drinks coffee. Who drinks milk?” For Developers A few lines of code. Million tokens. One call. --- ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed. - **Serverless:** scales to zero, scales to millions - **Pay per token,** no minimums - **Python and JavaScript SDKs,** plus REST API [API Documentation ](https://docs.modelslab.com) PythonJavaScriptcURL Copy ```

import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

``` FAQ Common questions about Qwen: Qwen3.5 Plus 2026-02-15 --- [Read the docs ](https://docs.modelslab.com) ### What is Qwen: Qwen3.5 Plus 2026-02-15? Qwen: Qwen3.5 Plus 2026-02-15 is a hosted API model with hybrid linear attention and MoE architecture. It supports 1M token context for text, image, video inputs. Released February 2026 by Alibaba. ### How does qwen qwen3 5 plus 2026 02 15 API compare to others? Matches Gemini 3 Pro performance at 1/18th cost. 19x faster than Qwen3-Max on 256k tasks. Outperforms in reasoning, coding, vision benchmarks. ### What context length for Qwen: Qwen3.5 Plus 2026-02-15 model? Supports 1,000,000 tokens, far exceeding standard 256k models. Enables long document analysis and extended conversations. ### Qwen: Qwen3.5 Plus 2026-02-15 alternative to what models? Direct alternative to Gemini 3 Pro, Claude 4.5, GPT-5.2 with lower cost and speed gains. Use for multimodal agent tasks. ### Does Qwen: Qwen3.5 Plus 2026-02-15 LLM support tools? Yes, Auto mode adaptively uses web search and code interpreter. Enable reasoning parameter for step-by-step thinking. ### qwen qwen3 5 plus 2026 02 15 API pricing details? Priced at 0.8 yuan per million tokens. Among cheapest for its speed and 88% benchmark success rate. Ready to create? --- Start generating with Qwen: Qwen3.5 Plus 2026-02-15 on ModelsLab. [Try Qwen: Qwen3.5 Plus 2026-02-15](/models/open_router/qwen-qwen3.5-plus-02-15) [API Documentation](https://docs.modelslab.com) --- *This markdown version is optimized for AI agents and LLMs.* **Links:** - [Website](https://modelslab.com) - [API Documentation](https://docs.modelslab.com) - [Blog](https://modelslab.com/blog) --- *Generated by ModelsLab - 2026-05-13*