Alibaba Qwen — Largest Model — August 4, 2026
20 free Qwen 3.8-Max prompts across vision analysis, long-document synthesis, agentic tool use, coding, and multimodal research. Copy directly into your Qwen app or API. No signup.
The Qwen 3.8-Max prompt generator on this page gives you 20 copy-paste prompts optimised for Alibaba's most capable AI model. Qwen3.8-Max launched August 4, 2026 as the largest model in the Qwen family — a Sparse MoE architecture with 2.4 trillion total parameters (95B active at inference) — and immediately claimed the #2 spot in Vision Arena globally. It accepts text, images, and video as input with a 1 million-token context window, making it one of the only models that can process a 200-page PDF or 100 hours of footage in a single request.
What makes Qwen3.8-Max unique for prompt engineering is its five built-in agentic tools: code_interpreter, web_search, web_extractor, t2i_search, and i2i_search. The prompts below are designed to unlock these capabilities — from live research and data extraction to image identification and code execution. Paste any prompt into chat.qwenlm.ai or your API call, then add your specific context in the brackets.
Data analysis, calculations, file parsing, chart generation. Qwen writes and executes Python in real time.
Current events, recent launches, competitor news, pricing. Use when you need information published after March 2026.
Pull structured data from any URL — product info, prices, contact details, or tabular data — returned as clean JSON.
Search for images by text description. Good for finding reference visuals, brand assets, or style examples for creative work.
Find similar images, identify products, places, or artworks by visual similarity. Upload an image and find what it is or where to get it.
Analyse entire books, annual reports, long video transcripts, or full codebases in a single request — no chunking needed.
Works with chat.qwenlm.ai and the QwenCloud API. Most prompts are also compatible with GPT-5.6, Claude Fable 5, and Gemini 4.
Analyse this image in full detail. Provide: 1. SUBJECT — who or what is the main subject, their position, expression, and activity 2. ENVIRONMENT — setting, lighting, time of day, and atmosphere 3. COMPOSITION — how elements are arranged and what draws the eye first 4. TECHNICAL — estimated focal length, depth of field, and camera angle 5. CONTEXT — what story does this image tell and what is happening just off-frame? [Attach your image]
I'm uploading a long document (up to 200 pages). Analyse it and return: 1. EXECUTIVE SUMMARY — 3-paragraph overview for a non-specialist 2. KEY FINDINGS — the 5 most important facts, conclusions, or claims 3. DATA HIGHLIGHTS — any specific numbers, statistics, or benchmarks cited 4. CONTRADICTIONS — any internal inconsistencies or claims that contradict each other 5. GAPS — what important questions does this document fail to answer? 6. ACTION ITEMS — what should I do differently after reading this? Document: [Attach your PDF or paste the full text]
Research the following topic using your web_search tool to gather current information, then synthesise a comprehensive brief: Topic: [your research question] Depth needed: [overview / detailed / expert-level] Output format: [bullet summary / structured report / comparison table] Steps: 1. Search for the 3 most authoritative current sources on this topic 2. Extract the key claims and data points from each 3. Synthesise into a unified view — what do sources agree on and where do they differ? 4. Flag any claims that are contested or lack strong evidence 5. Suggest 2 follow-up searches that would deepen the analysis
Use your code_interpreter tool to analyse this dataset and produce insights. Data: [paste CSV rows or describe the data structure] Questions to answer: 1. What is the distribution of [key column]? 2. Is there a correlation between [column A] and [column B]? 3. What are the top 5 outliers and why might they exist? 4. If this trend continues, what would the value of [metric] be in 6 months? Present results with: (a) the code you ran, (b) the output, (c) a plain-English interpretation of what each result means.
Watch this video clip and provide a structured breakdown: 1. OVERVIEW — what is this video about in one sentence? 2. SCENE LOG — timestamp-by-timestamp description of what happens (10-second intervals if under 2 min) 3. AUDIO — describe the speech, music, or ambient sound and what it communicates 4. KEY MOMENTS — the 3 most important frames or events and why they matter 5. CONTEXT — what platform is this for, who made it, and what is its likely purpose? [Attach your video file]
Analyse this financial report (annual report, earnings call transcript, or 10-K filing) and produce a structured investment brief: 1. REVENUE — growth rate, segments, and any acceleration or deceleration 2. MARGINS — gross, operating, and net margins vs. prior period 3. BALANCE SHEET — cash position, debt load, and liquidity 4. GUIDANCE — what management said about the next quarter and full year 5. RED FLAGS — any accounting notes, restatements, or disclosures that warrant closer attention 6. VERDICT — in one paragraph: is this business getting stronger or weaker? Report: [Attach the PDF or paste the text]
Use your web_extractor tool to extract structured data from the following URL and return it in JSON format: URL: [paste the URL] Fields to extract: - [field 1, e.g. 'product name'] - [field 2, e.g. 'price'] - [field 3, e.g. 'rating'] - [field 4, e.g. 'availability'] After extraction: 1. Show the raw JSON 2. Flag any fields that were missing or ambiguous 3. Note any data quality issues I should know about
Audit this codebase for architectural issues, security vulnerabilities, and performance bottlenecks. Code: [paste your code or describe the project structure] Stack: [your tech stack and versions] Scale: [approximate users/requests per day] Deliver: 1. ARCHITECTURE — how is the code structured? What patterns are used? 2. SECURITY — list every potential vulnerability with severity (Critical / High / Medium / Low) 3. PERFORMANCE — identify the top 3 bottlenecks and explain why each is a problem 4. TECH DEBT — what shortcuts were taken that will cause problems at 10x scale? 5. PRIORITY FIXES — the 5 changes I should make this week, in order of impact 6. QUICK WINS — 3 changes I can make in under an hour that will immediately improve quality
I'm sharing a brand image. Use it to generate a complete content marketing campaign brief: [Attach your brand image, product photo, or campaign visual] From this image, produce: 1. BRAND VOICE — 3 adjectives that describe the mood and tone 2. CAMPAIGN CONCEPT — a one-sentence creative idea that builds on the visual 3. HEADLINE OPTIONS — 5 ad headlines (under 8 words each) 4. BODY COPY — 100-word version and 30-word version for different placements 5. SOCIAL CAPTIONS — one for Instagram (with hashtags), one for LinkedIn, one for X 6. CALL TO ACTION — 3 CTA variants from soft to direct
I'm attaching multiple research papers on the same topic. Synthesise them into a structured literature review: Papers: [attach PDFs or paste abstracts + key sections] Topic: [the unifying subject] Deliver: 1. CONSENSUS — what every paper agrees on (cite which papers) 2. CONTRADICTIONS — where papers directly disagree and the probable reason 3. METHODOLOGY GAPS — what none of the papers tested that should have been tested 4. STRONGEST EVIDENCE — which paper has the most rigorous methodology and why 5. PRACTICAL TAKEAWAY — one paragraph for a practitioner who won't read the papers 6. NEXT RESEARCH QUESTION — the single most important unanswered question
Design a scalable system architecture for the following product: Product: [describe what it does] Current state: [how it works now, if anything exists] Scale target: [e.g. '10M users, 500K concurrent, 99.99% uptime'] Constraints: [budget, team size, preferred cloud provider] Deliver: 1. COMPONENT DIAGRAM — describe each service and how they connect 2. DATA MODEL — key tables/collections and their relationships 3. API DESIGN — the 5 most critical endpoints with request/response structure 4. FAILURE MODES — what breaks first at 10x load and how to prevent it 5. COST ESTIMATE — rough monthly cost at 1M users 6. MIGRATION PATH — how to get from current state to target with zero downtime
Summarise this legal document in plain language that a non-lawyer can understand and act on: Document: [attach contract, terms of service, NDA, or policy document] Provide: 1. PLAIN SUMMARY — what does this document actually obligate me to do? 2. RIGHTS I GAIN — what can I do because of this agreement? 3. RIGHTS I GIVE UP — what am I agreeing NOT to do or giving away? 4. RISK FLAGS — clauses that are unusual, one-sided, or commonly litigated 5. MISSING CLAUSES — what important protections are absent? 6. QUESTIONS FOR A LAWYER — the 3 things I should clarify before signing Do not give legal advice — summarise and flag, don't prescribe.
Develop a market entry strategy for the following product: Product: [describe it in one sentence] Target market: [geography, industry, customer type] Competitors: [list 3-5 existing players] Budget for launch: [rough range] Timeline: [when do we need traction?] Deliver: 1. MARKET SIZING — TAM, SAM, SOM estimates with your reasoning 2. POSITIONING — where in the market is there genuine white space? 3. GO-TO-MARKET — the first 90 days (week by week for the first month) 4. PRICING — 3 pricing model options with pros and cons of each 5. RISKS — the 3 most likely reasons this fails and how to mitigate each 6. NORTH STAR METRIC — the one number that tells us if this is working
Use your i2i_search tool to identify similar images or products to the one I'm sharing. [Attach your reference image] After searching, tell me: 1. What is this object/person/place — name and key details 2. Where can I find similar items (products, locations, styles) 3. The 3 closest visual matches you found and what makes them similar 4. Any relevant context: origin, creator, historical significance, or market value 5. If this is a product: approximate price range and where to buy
Write complete developer documentation for the following API / system / tool: What it does: [one sentence] Primary users: [who will use this documentation] Tech stack: [languages and frameworks involved] The documentation must include: 1. OVERVIEW — purpose, key concepts, and when to use this vs. alternatives 2. QUICK START — 5-step setup with copy-paste commands that actually work 3. CORE CONCEPTS — 3-5 terms defined, each with a concrete example 4. API REFERENCE — for each endpoint/function: parameters, return types, example request, example response, and error codes 5. COMMON PATTERNS — 3 real-world use cases with full code examples 6. TROUBLESHOOTING — the 5 most common errors and how to fix each Write for a developer who has never used this before and will be blocked if anything is unclear.
Use your web_search tool to research my competitors and produce a competitive intelligence report. My company: [one sentence description] Competitors to research: [list 3-5 companies or products] Key dimensions: [e.g. pricing, features, go-to-market, recent news, job postings] For each competitor: 1. What are they doing RIGHT NOW (search for news in the last 30 days)? 2. Where are they investing? (look for recent hires, fundraises, product launches) 3. What are customers saying? (search for reviews and complaints) 4. Where are they weak? (what can't they do that we can?) End with: the 1 threat and 1 opportunity I should act on this month.
I'm sharing multiple images from my website / marketing materials / social feed. Audit them for consistency, quality, and brand alignment. [Attach 3-10 images] For the set as a whole: 1. BRAND CONSISTENCY — do these look like they come from the same brand? What is inconsistent? 2. QUALITY ISSUES — which images are technically weak (resolution, lighting, composition)? 3. MESSAGE CLARITY — does each image immediately communicate what it's meant to? 4. AUDIENCE FIT — who is the implied audience and is the imagery appropriate for them? 5. STRONGEST IMAGE — which one works best and why? 6. PRIORITY CHANGES — the 3 images to replace first and what to replace them with
Use your t2i_search tool to research what makes effective prompts for [your target image generator — e.g. MidJourney, DALL-E, Flux], then help me refine my prompt. My current prompt: [paste your prompt] Target tool: [image generator name] Desired outcome: [describe what you want the image to look like] What's wrong with current results: [describe the problem] Deliverables: 1. DIAGNOSIS — what is my current prompt missing or doing wrong? 2. REFINED PROMPT — rewritten version with specific improvements 3. 3 VARIATIONS — different stylistic angles on the same concept 4. NEGATIVE PROMPTS — what to exclude to get cleaner results 5. PARAMETER SUGGESTIONS — any tool-specific settings to adjust
Build a 90-day content strategy for the following brand: Brand: [describe what you do and who you serve] Goal: [e.g. '50% more organic traffic', 'establish thought leadership', 'generate leads'] Current channels: [where you publish and approximate audience sizes] Resources: [how many hours per week, team size, budget for promotion] Deliver: 1. CONTENT PILLARS — 3-5 themes that connect your expertise to your audience's needs 2. FORMAT MIX — which content types to use and in what ratio (why each format serves the goal) 3. 90-DAY CALENDAR — at least 12 specific content titles with target keyword and channel 4. DISTRIBUTION PLAN — how to get each piece seen without relying on organic reach alone 5. SUCCESS METRICS — how to measure if this strategy is working after 30 / 60 / 90 days 6. QUICK WIN — one piece of content I could publish this week that would immediately drive results
Work through this multi-variable problem step by step, showing every assumption and calculation: Problem: [describe your problem — can be business, scientific, mathematical, or logistical] Constraints: - [constraint 1] - [constraint 2] - [constraint 3] Unknowns I need to solve for: [list what you want to find] Instructions: 1. State your assumptions explicitly before calculating anything 2. Break the problem into sub-problems and solve each in sequence 3. Show every step — don't skip to the answer 4. At the end, run a sanity check: does the answer make intuitive sense? 5. State the one assumption that, if wrong, would most change your answer
How Qwen3.8-Max compares to the other frontier models across the dimensions that matter for real-world tasks.
| Model | Strengths | Context | Vision Arena | Price (input/output) |
|---|---|---|---|---|
| Qwen 3.8-Max ✓ | Long video/doc analysis, vision, agentic tools, open API | 1M tokens | #2 globally | $2 / $6 per MTok |
| GPT-5.6 Sol | Best-in-class reasoning, coding, image gen integration | 256K tokens | #1 globally | $10 / $40 per MTok |
| Claude Fable 5 | Frontier reasoning, long creative tasks, safety alignment | 1M tokens | Top 5 | $10 / $50 per MTok |
| Gemini 4 | Google ecosystem, video natively, Search grounding | 1M tokens | Top 5 | $7 / $28 per MTok |
| Kimi K3 | 2.8T open-weight, strong reasoning, native vision | 1M tokens | Top 10 | $1 / $4 per MTok |
qwen3.8-max explicitlyQwen 3.8-Max is Alibaba's largest and most capable AI model, released August 4, 2026. It uses a Sparse Mixture-of-Experts (MoE) architecture with 2.4 trillion total parameters and 95 billion active parameters at inference time. It accepts text, image, and video as input and supports a 1 million-token context window — enough to analyse 200+ pages of text or 100 hours of footage in a single request. As of launch, Qwen3.8-Max ranks #5 in Text Arena and #2 in Vision Arena globally.
Qwen3.8-Max is Qwen's first 2T+ parameter model and their first to natively support video understanding alongside text and images. It also ships with five built-in agentic tools accessible via the Responses API: code_interpreter (run code), web_search (live internet access), web_extractor (structured data from URLs), t2i_search (text-to-image research), and i2i_search (image-to-image search). These tools make it significantly more capable for multi-step agentic tasks than any previous Qwen model.
Qwen3.8-Max is available via API on Alibaba Cloud Model Studio (QwenCloud) at $2 per million input tokens, $6 per million output tokens, and $0.25 per million cached tokens. It is OpenAI- and DashScope-compatible, so integration is a base-URL change and model ID substitution in any existing OpenAI SDK integration. It is also accessible through Alibaba's Qwen chat interface at chat.qwenlm.ai for direct use without API setup.
Yes — all 20 prompts on this page are free to copy and paste. To use them with Qwen3.8-Max, you need API access via QwenCloud ($2/$6 per MTok) or a Qwen app subscription. The prompts are also largely compatible with other capable multimodal models like GPT-5.6, Claude Fable 5, or Gemini 4 — adapt the tool-use prompts to whatever agentic tools your model supports.
As of August 2026, Qwen3.8-Max holds #2 globally in Vision Arena (behind GPT Image 2 / GPT-5.6 on image understanding tasks). On Terminal-Bench 2.1, it scores 86.6 — ahead of Claude Fable 5 (84.6) and Claude Opus 4.8, but behind GPT-5.6 Sol (88.8). Its strongest performance areas are long-context analysis, vision understanding, coding, and agentic multi-step tasks.
Qwen3.8-Max has a 1 million-token context window, enough to process approximately 750,000 words, a multi-hundred-page financial report, or approximately 100 hours of video content in a single request. The model builds continuous memory graphs over very long video streams, making it especially powerful for analysing lengthy recordings like lectures, earnings calls, or documentary footage.
Moonshot AI's 2.8T open-weight model — 20 reasoning prompts
Anthropic's frontier model — 20 prompts for the hardest tasks
Google's everyday multimodal workhorse — 20 prompts
OpenAI's multi-tier frontier model — 20 copy-paste prompts
Thinking Machines Lab 975B open-weight — 20 multimodal prompts
Open-weight powerhouse for coding & agents — 20 prompts