---
id: "qwen/qwen3.6-27b"
also: ["qwen/qwen3.6-27b-20260422", "Qwen/Qwen3.6-27B", "hf/Qwen/Qwen3.6-27B", "vercel/alibaba/qwen3.6-27b"]
cheapest_list_usd_per_m: "0.25 in, 2.0 out, at chutes/fp8 on openrouter"
cheapest_effective_usd_per_m: "0.0977 in, 2.0 out, at chutes/fp8 on openrouter"
context: 262144
max_output: 81920
input: ["text", "image", "video"]
output: ["text"]
released: "2026-04-27"
api: ["/api/v1/chat/completions", "/api/v1/completions", "/api/v1/messages", "/api/v1/responses"]
params: ["frequency_penalty", "include_reasoning", "logit_bias", "logprobs", "max_tokens", "min_p", "presence_penalty", "reasoning", "repetition_penalty", "response_format", "seed", "stop", "structured_outputs", "temperature", "tool_choice", "tools", "top_k", "top_logprobs", "top_p"]
endpoints: 14
gateways: "openrouter (10), hf (3), vercel (1)"
no_training: 9
trains: 0
retains_prompts: 2
coding: 53.7000
agentic: 18.5000
---
# Qwen: Qwen3.6 27B

The Qwen3.6 35B-A3B native vision-language model is built on a hybrid architecture that integrates linear attention mechanisms with a sparse mixture-of-experts framework, achieving higher inference efficiency. Compared with the 3.5-35B-A3B, this model demonstrates significantly improved agentic coding capabilities, mathematical and code reasoning abilities, spatial intelligence, as well as object localization and object detection performance.