Qwen3.5-27B is a 27 billion parameter multimodal model that blends vision and language through early fusion training on multimodal tokens, built on a hybrid architecture of Gated DeltaNet and Mixture-of-Experts layers. It supports a 262,144 token native context window, extensible toward roughly one million tokens with YaRN scaling. Reported scores include MMLU-Pro 86.1, GPQA Diamond 85.5, SWE-bench Verified 72.4, and MathVista 86.0, reflecting balanced strength across reasoning, coding, and visual understanding. It runs in thinking mode by default, generating reasoning before responses. The model handles text, image, and video inputs across more than 200 languages, suiting knowledge-intensive problems, agentic coding, and multimodal reasoning.
Qwen3.5 27B runs on 2 different routes through the qynio gateway. Compare residency, zero retention, and training posture at a glance β full data-handling detail per route below.
Qwen3.5 27B runs on 2 independently monitored routes through the qynio gateway. A direct integration leaves you on one of them, the gateway serves whichever is healthy.
Measured over the last 30 days from each provider's official status feed via StatusGator. Refreshed hourly. See uptime for every provider qynio monitors.
Each route hosting Qwen3.5 27B has its own privacy posture, residency, and no-KYC terms. Postures are maintained by qynio with a last-verification timestamp.
Zero data retention is on by default on Pay-as-you-go β no action required. No training on customer data. US; unknown; deposit available.
Zero data retention is on by default on Pay-as-you-go β no action required. No training on customer data. US; wallets; deposit available.
Independent benchmark scores β composite indices for reasoning, coding, and math, plus individual eval scores where available.
Call Qwen3.5 27B through the qynio gateway with one API key. Let your coding agent set it up, or call it directly β qynio is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.
Copy this and paste it into a coding agent like Claude Code, Cursor or Codex and it'll wire up qynio for you.
import OpenAI from "openai";const client = new OpenAI({apiKey: process.env.QYN_API_KEY,baseURL: "https://api.qyn.io/v3/compat",});const completion = await client.chat.completions.create({model: "deepinfra/Qwen/Qwen3.5-27B",messages: [{ role: "user", content: "Hello" }],});console.log(completion.choices[0].message.content);
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