Qwen 3.6 27B
A 27B dense multimodal model from Alibaba's Qwen team, optimized for agentic coding, reasoning, and long-context tasks.
Get API key- Provider
- Qwen (Alibaba Group)
- Price
- $0.33 in · $3.25 out / 1M
- Context window
- 256K tokens
- Released
- April 21, 2026
- License
- Proprietary
What is Qwen 3.6 27B?
Qwen 3.6 27B is a 27-billion-parameter dense language model from Alibaba's Qwen team, released in April 2026. It supports vision, reasoning, tool use, and web search, offers a 256K context window, and is optimized for agentic coding and repository-level reasoning.
Use it privately on Venice
On Venice, Qwen 3.6 27B runs with zero retention — your prompts are not stored or profiled. You get full access to its vision, reasoning, web search, and tool-use capabilities, plus structured JSON output and multi-image inputs, all under a private, permissionless inference tier with no Big-Tech surveillance.
What can it do?
- •Agentic coding — strong at repository-level reasoning and frontend workflows.
- •Multimodal — supports vision, video, multiple image inputs, and structured JSON output.
- •Long context — 256K context window for large codebases and documents.
- •Reasoning — built-in reasoning mode with thinking preservation across conversation history.
- •Tool use — native function calling and web search integration for autonomous workflows.
- •Efficient dense architecture — flagship-level performance in a 27B parameter footprint.
- •Closed weights — not open-source, so it cannot be self-hosted or fine-tuned outside Venice.
- •Output pricing — at $3.25 per 1M output tokens, it is more expensive than open-weight rivals such as DeepSeek V3.2.
- •Dense model — lacks the active-parameter efficiency of MoE alternatives, so inference costs scale with the full 27B.
- •Quantization — runs at FP8 on Venice, which may slightly reduce precision compared to higher-precision formats.
Qwen 3.6 27B capabilities
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
How to use it via API
Venice exposes an OpenAI-compatible API. Swap your base URL and call qwen3-6-27b.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-6-27b",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Specifications
Pricing
Billed per token on Venice: $0.33 per 1M input tokens and $3.25 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Qwen 3.6 27B vs alternatives
| Model | Context window | Strongest at | Open weights | Price (Venice) |
|---|---|---|---|---|
| Qwen 3.6 27B | 256K tokens | Agentic coding & reasoning | No | $0.33 in · $3.25 out / 1M |
| DeepSeek V3.2 | 160K tokens | General reasoning & value | Yes | $0.33 in · $0.48 out / 1M |
| Google Gemma 4 31B Instruct | 256K tokens | Lightweight open inference | Yes | $0.12 in · $0.36 out / 1M |
| Kimi K2.6 | 256K tokens | Long-context open weights | Yes | $0.75 in · $3.50 out / 1M |
Dense flagship with vision, tool use, reasoning, and web search.
What is it good for?
- •Agentic software development and repository-level coding assistants.
- •Multimodal analysis of images, video, and documents with structured output.
- •Long-context research and document Q&A over large codebases or reports.
- •Iterative reasoning tasks where thinking preservation across turns matters.
- •Automated workflows using tool use, web search, and function calling.
Prompting tips
- •Enable reasoning mode for complex coding or math problems to leverage thinking preservation.
- •Use structured JSON schema output for parsing logs, APIs, or tabular data.
- •For code generation, provide repository context in the first prompt to exploit the 256K window.
- •When using vision, upload multiple images in a single turn for comparative analysis.
Version history
Prior series.
CurrentCurrent dense release with vision and agentic coding.
Frequently asked questions
Qwen 3.6 27B is a 27-billion-parameter dense language model from Alibaba's Qwen team, released in April 2026. It supports text, vision, reasoning, tool use, and web search, and is optimized for agentic coding and long-context workflows.
On Venice, Qwen 3.6 27B is billed at $0.33 per 1M input tokens and $3.25 per 1M output tokens. You pay only for what you use with no subscription required.
It is not free — usage is billed per token. It is also not open weights; the model is proprietary and cannot be downloaded or self-hosted.
Yes. It supports function calling, structured JSON output, web search, and vision inputs including multiple images and video.
Qwen 3.6 27B leads on agentic coding, vision, and reasoning with a 256K context window. DeepSeek V3.2 is fully open weights and significantly cheaper per output token, making it ideal for self-hosting and cost-sensitive scale.
Yes. Venice runs it under a zero-retention privacy tier — your prompts are not stored, profiled, or used for training.
Yes, the model accepts video input as well as multiple images, making it suitable for multimodal analysis and workflows.
The model supports up to 256K tokens of context on Venice, with a maximum output of 65,536 tokens per generation.
Related models
Run Qwen 3.6 27B privately.
No prompt logging. No data used for training. Free to start — no credit card.
