Qwen3.6-35B-A3B: Agentic Coding Power, Now Open to All

QWEN STUDIO HUGGING FACE MODELSCOPE DISCORD

Following the launch of Qwen3.6-Plus, we are excited to open-source Qwen3.6-35B-A3B — a sparse yet remarkably capable mixture-of-experts (MoE) model with 35 billion total parameters and only 3 billion active parameters. Despite its efficiency, Qwen3.6-35B-A3B delivers outstanding agentic coding performance, surpassing its predecessor Qwen3.5-35B-A3B by a wide margin and rivaling much larger dense models such as Qwen3.5-27B and Gemma4-31B. Still supporting both multimodal thinking and non-thinking modes, Qwen3.6-35B-A3B works as one of the most versatile open-source models available today. Now, Qwen3.6-35B-A3B is live on Qwen Studio, available through our API, and released as open weights for the community.

• Qwen3.6-35B-A3B is a fully open-source MoE model (35B total / 3B active), featuring:
  • exceptional agentic coding capability competitive with much larger models
  • strong multimodal perception and reasoning ability
• You can chat interactively on Qwen Studio, call via API as Qwen3.6-Flash on Alibaba Cloud Model Studio API (coming soon), or download weights from Hugging Face and ModelScope.

Performance

Below we present comprehensive evaluations of Qwen3.6-35B-A3B against peer-scale models across a wide range of tasks and modalities.

Language

With only 3B active parameters, Qwen3.6-35B-A3B outperforms the dense 27B-parameter Qwen3.5-27B on several key coding benchmarks and dramatically surpasses its direct predecessor Qwen3.5-35B-A3B, especially on agentic coding and reasoning tasks.

Vision Language

Qwen3.6 is natively multimodal, and Qwen3.6-35B-A3B showcases perception and multimodal reasoning capabilities that far exceed what its size would suggest, with only around 3 billion activated parameters. Across most vision-language benchmarks, its performance matches Claude Sonnet 4.5, and even surpasses it on several tasks. Its strengths are particularly evident in spatial intelligence, where it achieves 92.0 on RefCOCO and 50.8 on ODInW13.

Build with Qwen3.6-35B-A3B

Qwen3.6-35B-A3B is coming soon to Alibaba Cloud Model Studio. Please stand by until we are fully ready.

Qwen3.6-35B-A3B is available as open weights on Hugging Face and ModelScope for self-hosting, and through the Alibaba Cloud Model Studio API as qwen3.6-flash. You can also try it instantly on Qwen Studio.

The model can be seamlessly integrated with popular third-party coding assistants, including OpenClaw, Claude Code, and Qwen Code, to streamline development workflows and enable efficient, context-aware coding experiences.

API Usage

This release supports the preserve_thinking feature: preserving thinking content from all preceding turns in messages, which is recommended for agentic tasks.

Alibaba Cloud Model Studio

Alibaba Cloud Model Studio supports industry-standard protocols, including chat completions and responses APIs compatible with OpenAI's specification, as well as an API interface compatible with Anthropic.

Example code for chat completions API is provided below:

python
""" Environment variables (per official docs):  DASHSCOPE_API_KEY: Your API Key from https://modelstudio.console.alibabacloud.com  DASHSCOPE_BASE_URL: (optional) Base URL for compatible-mode API.  - Beijing: https://dashscope.aliyuncs.com/compatible-mode/v1  - Singapore: https://dashscope-intl.aliyuncs.com/compatible-mode/v1  - US (Virginia): https://dashscope-us.aliyuncs.com/compatible-mode/v1  DASHSCOPE_MODEL: (optional) Model name; override for different models. """from openai import OpenAIimport os
api_key = os.environ.get("DASHSCOPE_API_KEY")if not api_key: raise ValueError( "DASHSCOPE_API_KEY is required. " "Set it via: export DASHSCOPE_API_KEY='your-api-key'" )
client = OpenAI( api_key=api_key, base_url=os.environ.get( "DASHSCOPE_BASE_URL", "https://dashscope-intl.aliyuncs.com/compatible-mode/v1", ),)
messages = [{"role": "user", "content": "Introduce vibe coding."}]
model = os.environ.get( "DASHSCOPE_MODEL", "qwen3.6-flash",)completion = client.chat.completions.create( model=model, messages=messages, extra_body={ "enable_thinking": True, # "preserve_thinking": True, }, stream=True)
reasoning_content = "" # Full reasoning traceanswer_content = "" # Full responseis_answering = False # Whether we have entered the answer phaseprint("\n" + "=" * 20 + "Reasoning" + "=" * 20 + "\n")
for chunk in completion: if not chunk.choices: print("\nUsage:") print(chunk.usage) continue
 delta = chunk.choices[0].delta
 # Collect reasoning content only if hasattr(delta, "reasoning_content") and delta.reasoning_content is not None: if not is_answering: print(delta.reasoning_content, end="", flush=True) reasoning_content += delta.reasoning_content
 # Received content, start answer phase if hasattr(delta, "content") and delta.content: if not is_answering: print("\n" + "=" * 20 + "Answer" + "=" * 20 + "\n") is_answering = True print(delta.content, end="", flush=True) answer_content += delta.content

For more information, please visit the API doc.

Coding & Agents

Qwen3.6-35B-A3B features excellent agentic coding capabilities and can be seamlessly integrated into popular third-party coding assistants, including OpenClaw, Claude Code, and Qwen Code.

OpenClaw

Qwen3.6-35B-A3B is compatible with OpenClaw (formerly Moltbot / Clawdbot), a self-hosted open-source AI coding agent. Connect it to Model Studio to get a full agentic coding experience in the terminal. Get started with the following script:

bash
# Node.js 22+curl -fsSL https://molt.bot/install.sh | bash # macOS / Linux
# Set your API keyexport DASHSCOPE_API_KEY=<your_api_key> 
# Launch OpenClawopenclaw dashboard # web browser# openclaw tui # Open a new terminal and start the TUI

On first use, edit ~/.openclaw/openclaw.json to point OpenClaw at Model Studio. Find or create the following fields and merge them — do not overwrite the entire file to preserve your existing settings:

json
{ "models": { "mode": "merge", "providers": { "modelstudio": { "baseUrl": "https://dashscope-intl.aliyuncs.com/compatible-mode/v1", "apiKey": "DASHSCOPE_API_KEY", "api": "openai-completions", "models": [ { "id": "qwen3.6-flash", "name": "qwen3.6-flash", "reasoning": true, "input": ["text", "image"], "contextWindow": 131072, "maxTokens": 16384 } ] } } }, "agents": { "defaults": { "model": { "primary": "modelstudio/qwen3.6-flash" }, "models": { "modelstudio/qwen3.6-flash": {} } } }}

Qwen Code

Qwen3.6-35B-A3B is compatible with Qwen Code, an open-source AI agent designed for the terminal and deeply optimized for the Qwen Series. Get started with the following script:

bash
# Node.js 20+npm install -g @qwen-code/qwen-code@latest 
# Start Qwen Code (interactive)qwen 
# Then, in the session:/help /auth 

On first use, you'll be prompted to sign in. You can run /auth anytime to switch authentication methods.

Claude Code

Qwen APIs also support the Anthropic API protocol, meaning you can use it with tools like Claude Code for elevated coding experience:

bash
# Install Claude Codenpm install -g @anthropic-ai/claude-code 
# Configure environmentexport ANTHROPIC_MODEL="qwen3.6-flash"export ANTHROPIC_SMALL_FAST_MODEL="qwen3.6-flash"export ANTHROPIC_BASE_URL=https://dashscope-intl.aliyuncs.com/apps/anthropic export ANTHROPIC_AUTH_TOKEN=<your_api_key> 
# Launch the CLIclaude 

Summary

Qwen3.6-35B-A3B demonstrates that sparse MoE models can achieve remarkable agentic coding and reasoning capability. With only 3B active parameters, it delivers performance that rivals dense models several times its active size, while also excelling across multimodal benchmarks. As a fully open-source checkpoint, it sets a new standard for what's possible at its scale.

Looking ahead, we will continue to expand the Qwen3.6 open-source family and push the boundaries of what efficient, open models can accomplish. We are grateful for the community's feedback and look forward to seeing what you build with Qwen3.6-35B-A3B. Also, Qwen3.6 open-source family keeps expanding, stay tuned for our future releases!

Citation

Feel free to cite the following article if you find Qwen3.6-35B-A3B helpful:

bibtex
@misc{qwen36_35b_a3b, title = {{Qwen3.6-35B-A3B}: Agentic Coding Power, Now Open to All}, url = {https://qwen.ai/blog?id=qwen3.6-35b-a3b}, author = {{Qwen Team}}, month = {April}, year = {2026}}