Chrome ExtensionQwen Prompt Generator
Updated for Qwen3.8 — Qwen3.8-Max (August 2026) plus the open-weight 2.4T-A95B, 27B and Flash-Next models. Generate optimized prompts for Alibaba's Qwen with a model picker, Thinking toggle, 119+ language support, Chinese-English bilingual work and MCP tool integration. Prompts work in the Qwen app, Qwen Chat, the API and self-hosted open-weight deployments.
Be specific about what you want the AI to do
Generated Prompt
Fill in the form and click "Generate" to create an optimized Qwen (Qwen3.8) prompt.
Tip: The more specific your task description and context, the better the generated prompt will perform.
Qwen (Qwen3.8) Tips
- • Qwen3.8-Max is the flagship: a 2.4-trillion-parameter MoE model (about 95B active) with a 1M-token context and text, image and video input
- • Thinking ON for math, complex coding, or when accuracy matters; OFF for speed. The open Qwen3.8-2.4T-A95B weights have no non-thinking mode, so they always reason
- • The open Qwen3.8 models expose reasoning_effort (low / medium / xhigh) — on the 27B, xhigh is the default; drop to low when speed and cost matter more than depth
- • Qwen is exceptional at Chinese-English bilingual work — name the target language(s) explicitly
- • Qwen supports 119+ languages — for low-resource languages, give Qwen 1-2 example sentences to anchor style
- • For coding, name language, framework, version, dependencies, and coding standards precisely
- • For math, ask Qwen to "show every step and recompute the final answer before stating it"
- • Qwen3.8-Max reads up to 1M tokens — paste long sources/docs/codebases, then put your instruction at the end
- • The open-weight Qwen3.8-2.4T-A95B is text only — describe images in words or use Qwen3.8-Max / Qwen3.8-27B for visual input
Qwen3.8 Prompt Templates
Copy-ready starting points for the most common jobs people bring to this model. Swap the [BRACKETED] parts for your own details, or use them as a shape to imitate when you write your own.
Bilingual Business Document
LanguageQwen's Chinese/English mastery with an explicit register per language.
Produce [DELIVERABLE] about [TOPIC] in both [LANGUAGE A] and [LANGUAGE B]. Audience: [AUDIENCE]. Register: [FORMAL / BUSINESS / CASUAL]. Requirements: - Write each version natively — do not translate one into the other. - Keep [TERMS / PRODUCT NAMES] identical across both. - Match length within [TOLERANCE]. Format: [LANGUAGE A] version first, then a separator, then [LANGUAGE B].
Thinking-Mode Problem
ReasoningFramed so Qwen's hybrid Thinking mode has something to work on.
Problem: [THE PROBLEM] Given: [KNOWNS]. Find: [UNKNOWN]. Constraints: [CONSTRAINTS]. Reason through this step by step, checking each intermediate result before moving on. Verify the final answer against the constraints and state whether it satisfies all of them. If the problem is underspecified, say what is missing instead of assuming.
MCP Tool Workflow
AgenticQwen ships MCP integration — name the servers and the calling policy.
Goal: [THE END STATE] Available MCP tools: - [SERVER/TOOL] — [what it provides, when to use it] - [SERVER/TOOL] — [what it provides, when to use it] Policy: query a tool rather than relying on memory for anything that could be stale; chain calls where one result feeds the next; report which tool produced each fact. Constraints: [CONSTRAINTS]. Return the result plus a short trace of the calls you made.
Code with Full Spec
EngineeringComplete specification, Qwen's preferred coding input.
Write [WHAT] in [LANGUAGE + VERSION]. Framework: [FRAMEWORK]. Dependencies allowed: [LIST]. Style: [CONVENTION]. Behaviour: [NUMBERED REQUIREMENTS] Edge cases: [LIST] Performance target: [TARGET] Return the implementation, then the tests, then a note on any requirement you could not satisfy and why.
Multilingual Content Localisation
LanguageUses Qwen's 119+ language coverage with cultural adaptation rules.
Localise the content below for [TARGET MARKET] in [LANGUAGE]. This is localisation, not translation. Adapt: - Examples and references to ones the target audience recognises - Units, currency, date formats - Idioms — replace rather than translate literally Do NOT change: [PRODUCT NAMES / LEGAL TEXT / FIGURES]. Flag anything that does not transfer culturally and explain the issue. Content: [PASTE CONTENT]
Long-Document Summary
AnalysisContext-first placement for long inputs.
[PASTE LONG DOCUMENT] --- Based on the document above, produce [DELIVERABLE] for [AUDIENCE]. Must include: [ESSENTIAL POINTS]. Target length: [LENGTH]. Output language: [LANGUAGE]. Cite the section behind each point. Do not add interpretation the document does not support.
Qwen Model & Prompting Update Log
Qwen3.8-Omni-Flash & Qwen 4 announcement
● LatestSeptember 18–22, 2026- Qwen3.8-Omni-Flash (September 18) is a native omni-modal model with a 1M-token context that takes text, image, audio and video input. It is built for agent work such as video editing, audio-visual summaries and real-time conversation, and is available through Alibaba Cloud Model Studio.
- At the Apsara Conference on September 22, Alibaba said the Qwen 4 family is in training. There is no release date, price or context window yet, so Qwen3.8 remains the current generation.
Open weights: Qwen3.8-2.4T-A95B, 27B & Flash-Next
August 12–26, 2026- August 12: the flagship's weights were released as Qwen3.8-2.4T-A95B. They are text only and have no non-thinking mode. Providers earning more than US$50M in 12 months need a commercial licence.
- August 14: Qwen3.8-27B, a vision-language model under Apache 2.0 with a 262K native context (extendable to 1M). Thinking is on by default, can be switched off per request, and depth is set with reasoning_effort (low, medium or xhigh, the default).
- August 26: Qwen3.8-Flash-Next, a multimodal MoE model with 6B active parameters that previews the Qwen 4 architecture. It supports enable_thinking and reasoning_effort.
- Recommended sampling on the 27B model card: temperature 1.0 with thinking on, 0.7 with it off.
Qwen3.8-Max
July 19 (preview) · August 3, 2026 (release)- Alibaba previewed Qwen3.8-Max at WAIC in Shanghai on July 19 and made it generally available in the cloud on August 3, 2026.
- It is a 2.4-trillion-parameter Mixture-of-Experts model with about 95B parameters active per token and a context window of up to 1M tokens.
- It is the first Qwen model above one trillion parameters to take text, images and video in one model.
- API pricing is a flat $2 per 1M input tokens and $6 per 1M output tokens.
How to Use the Prompt Generator
Define Your Task
Pick the Qwen3.8 model you will use, select a category, describe your task, and assign a role. Toggle Thinking ON for math, coding, or accuracy-critical work — leave it OFF for speed.
Set Language & Tools
Pick the output language (or Bilingual EN+ZH for Chinese-English work). If you have MCP tools attached, list them so Qwen knows when to call each.
Generate & Use
Click Generate. Paste the result into the Qwen app, Qwen Chat, the Alibaba Cloud DashScope API, or your self-hosted open-weight deployment.
Frequently Asked Questions
What is Qwen?
Qwen (formerly Tongyi Qianwen) is Alibaba's family of large language models. As of February 2026, Alibaba unified all of its consumer AI under the single "Qwen" brand. Qwen ships with hybrid Thinking modes, broad multilingual coverage (119+ languages and dialects), exceptional Chinese-English bilingual capability, Model Context Protocol (MCP) tool integration, and competitive coding/math performance. Open-weight Qwen models are also available for self-hosting.
What's new in Qwen3.8?
Alibaba previewed Qwen3.8-Max on July 19, 2026 at WAIC in Shanghai and released it in the cloud on August 3, 2026. It is a 2.4-trillion-parameter Mixture-of-Experts model with about 95B parameters active per token, a context window of up to 1M tokens, and native text, image and video input. API pricing is reported at $2 per 1M input tokens and $6 per 1M output tokens. On August 12, Alibaba released its weights as Qwen3.8-2.4T-A95B (text only, no non-thinking mode, and a commercial licence is required for providers earning more than US$50M a year). Qwen3.8-27B followed on August 14 under Apache 2.0, then Qwen3.8-Flash-Next on August 26 and Qwen3.8-Omni-Flash, an audio-video model with a 1M-token context, on September 18.
Which Qwen3.8 model should I pick?
Use Qwen3.8-Max (Qwen Chat or the Alibaba Cloud API) for the hardest reasoning, coding and long-document work, and whenever you need image or video input. Use Qwen3.8-27B if you want an Apache 2.0 model you can run yourself; it takes text, images and video, has a 262K native context (extendable to 1M), and lets you set reasoning_effort. Use Qwen3.8-Flash-Next for cheap, fast self-hosted coding and office tasks. Use Qwen3.8-Omni-Flash for audio and video understanding. Pick the model in the "Qwen Model" field and the generator adjusts the prompt.
Is Qwen 4 out?
No. On September 22, 2026, at the Apsara Conference, Alibaba said the Qwen 4 family is in training. It has no release date, pricing, context window or public benchmarks yet. Qwen3.8 is the current generation, and prompts built here for it should carry over.
What is Thinking mode?
Qwen's hybrid Thinking mode lets you toggle reasoning ON or OFF. Thinking ON makes Qwen reason step-by-step and verify before answering — pick this for math, complex coding, ambiguous briefs, and any task where accuracy matters. Thinking OFF keeps responses tight and fast — pick this for chat, quick lookups, or when latency matters. The open Qwen3.8 models also accept a reasoning_effort setting to tune how much they think, and the open Qwen3.8-2.4T-A95B weights have no non-thinking mode at all.
How does this prompt generator work?
You provide structured inputs — task, role, context, audience, constraints, Thinking toggle, output language, and any MCP tools. Our AI applies Qwen-specific 2026 best practices: clear task + format up front, role assignment, mode-aware framing, instruction-after-context placement for long inputs, and explicit verification directives for math/code.
Why is Qwen good at Chinese-English bilingual work?
Qwen was developed by Alibaba in China and trained heavily on Chinese as well as English. It handles tone, idiom, and technical terminology in both languages much better than most Western models. For bilingual output, name the format ("English answer first, then Mandarin translation, then a glossary of technical terms in both"). This generator builds that scaffolding automatically.
What is MCP?
MCP (Model Context Protocol) is a standard for connecting AI models to tools, data sources, and workflows. Qwen supports MCP, so you can paste in tool definitions and ask Qwen to use them. When you fill in the MCP / Tool Use field, this generator names those tools in the prompt and tells Qwen when to use each.
Is this tool free to use?
Yes. You get 1 free prompt generation per day with no signup required. For unlimited access, sign up for a Promptslove membership which includes all AI tools and 29,000+ premium prompts.
Where can I use the generated prompts?
The prompts work with the Qwen app, Qwen Chat, the Alibaba Cloud DashScope API, OpenRouter, Hugging Face Spaces, and self-hosted open-weight Qwen deployments. They also drop cleanly into other tools — ChatGPT, Claude, Gemini, MiniMax, Kimi, DeepSeek — because the structure is universal.
Is Qwen open source?
Many Qwen models are open-weight. In the Qwen3.8 generation, Qwen3.8-27B is Apache 2.0, Qwen3.8-Flash-Next weights are on Hugging Face and ModelScope, and the flagship's weights are available as Qwen3.8-2.4T-A95B (text only, and providers earning more than US$50M a year need a commercial licence). Qwen3.8-Max in the cloud and Qwen3.8-Omni-Flash are hosted by Alibaba. Prompts produced here work in either deployment.
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