Qwickly forging AGI, enhancing intelligence.
Users praise Alibaba Qwen for its outstanding coding capabilities and performance that surpass its size, especially in agentic coding and multimodal perception. The latest models are noted for their strong integration of diverse modalities like text, image, audio, and video, positioning them as versatile tools in the AI space. There are no key complaints mentioned, suggesting a generally positive reception. Pricing sentiment is not explicitly addressed in the available data, but the open-source availability under Apache 2.0 license could imply a positive outlook on accessibility. Overall, Qwen is gaining a strong reputation for innovation and high performance in the AI community.
Mentions (30d)
16
2 this week
Reviews
0
Platforms
3
GitHub Stars
20,881
1,754 forks
Users praise Alibaba Qwen for its outstanding coding capabilities and performance that surpass its size, especially in agentic coding and multimodal perception. The latest models are noted for their strong integration of diverse modalities like text, image, audio, and video, positioning them as versatile tools in the AI space. There are no key complaints mentioned, suggesting a generally positive reception. Pricing sentiment is not explicitly addressed in the available data, but the open-source availability under Apache 2.0 license could imply a positive outlook on accessibility. Overall, Qwen is gaining a strong reputation for innovation and high performance in the AI community.
Features
Use Cases
Industry
information technology & services
Employees
160
15,611
GitHub followers
40
GitHub repos
20,881
GitHub stars
20
npm packages
6
HuggingFace models
🚀 Meet Qwen3.6-27B, our latest dense, open-source model, packing flagship-level coding power! Yes, 27B, and Qwen3.6-27B punches way above its weight. 👇 What's new: 🧠 Outstanding agentic coding —
🚀 Meet Qwen3.6-27B, our latest dense, open-source model, packing flagship-level coding power! Yes, 27B, and Qwen3.6-27B punches way above its weight. 👇 What's new: 🧠 Outstanding agentic coding — surpasses Qwen3.5-397B-A17B across all major coding benchmarks 💡 Strong https://t.co/S36dggCCwk
View originalWeekly AI roundup (May 23–30, 2026): Claude Opus 4.8 Fast Mode 3x cheaper, Qwen 3.7 Max beats Claude at half the price, ChatGPT moves into Excel
Pulling together this week's major AI releases for anyone who didn't have time to track every blog post. Sticking to substantive changes, not hype. Anthropic — Claude Opus 4.8 Released this week. Headline pricing unchanged, but Fast Mode dropped from $30 input / $150 output per million tokens to $10 / $50 — a 3x reduction on the premium tier. Reported improvements in "judgment" and longer autonomous runs. Also shipped 20+ legal MCP connectors and Microsoft 365 add-ins (Excel, PowerPoint, Word) in GA. Alibaba — Qwen 3.7 Max Launched May 20 at Alibaba Cloud Summit. 1M-token context. Reported to top Claude Opus 4.6 Max on Terminal-Bench 2.0, SWE-Bench Pro, and MCP-Atlas. Pricing $2.50 / $7.50 per million tokens — roughly half of Opus 4.7. Alibaba claims autonomous operation up to 35 hours without performance degradation. Alibaba is now ranked #6 lab globally on Arena text leaderboard. OpenAI — GPT-5.5 Instant Now default in ChatGPT. Reports 52.5% fewer hallucinated claims than GPT-5.3 Instant on high-stakes prompts (medicine, law, finance). OpenAI also shipped a ChatGPT sidebar inside Excel and Google Sheets, plus a personal finance dashboard for Pro users (US only). Google — Gemini 3.5 Flash Reported to beat Gemini 3.1 Pro on coding and agentic benchmarks at ~4x faster output token rate. Ultra subscription cut from $250 to $200/month; new $100/month Developer tier introduced. xAI — Grok Build 0.1 Coding agent moved to public API beta May 28. Custom Skills feature added for reusable user-defined tasks. Connectors for SharePoint, OneDrive, Notion, GitHub, Linear, plus bring-your-own MCP support. Mistral Launched Vibe (unified work + code agent, replaces Le Chat). Acquired Emmi AI for physics-based simulation. Targeting €1B revenue in 2026; new 10MW inference DC announced. Hugging Face Launched an app store for the Reachy Mini robot. ~10,000 units shipped. Also reported a malicious repo masquerading as an OpenAI release that accumulated 244K downloads before takedown — relevant for anyone pinning models from HF in production. My take as someone building on top of these APIs: The 3x Opus Fast Mode price cut and Qwen 3.7 Max's pricing + autonomous duration are the real signal this week. The cost floor on premium-tier inference is dropping faster than most app-layer products have repriced for. Anyone running multi-step agent workflows needs to recompute unit economics this week — either pass through the savings or reinvest the margin. The other pattern worth noting: OpenAI and Anthropic are both pushing into Excel/M365 surfaces. Distribution is becoming the next battleground, not raw model capability. If you're building a productivity SaaS, the giants are now inside the same surface as you. submitted by /u/ksraj1001 [link] [comments]
View original✅Implicit caching is now live on Qwen3.7-Max — kicks in automatically, no setup needed. ⚡️Faster + cheaper out of the box. Need higher, more deterministic hit rates? Try explicit caching instead. 🙌
✅Implicit caching is now live on Qwen3.7-Max — kicks in automatically, no setup needed. ⚡️Faster + cheaper out of the box. Need higher, more deterministic hit rates? Try explicit caching instead. 🙌 🔗Best practices 🔗 :https://t.co/3hSs6zquBH
View original🚀Qwen3.7-Max just landed at 56.6 on the Artificial Analysis Intelligence Index — a solid 4.8pt jump over Qwen3.6-Max-Preview. @ArtificialAnlys ⚡️Sharper sci reasoning, stronger agentic chops, bette
🚀Qwen3.7-Max just landed at 56.6 on the Artificial Analysis Intelligence Index — a solid 4.8pt jump over Qwen3.6-Max-Preview. @ArtificialAnlys ⚡️Sharper sci reasoning, stronger agentic chops, better coding, and it hallucinates less.
View originalCowork Productivity Assistant:Qwen3.7-Max serves as your advanced coworker for real-world productivity. https://t.co/zFOjvNJAhT
Cowork Productivity Assistant:Qwen3.7-Max serves as your advanced coworker for real-world productivity. https://t.co/zFOjvNJAhT
View originalSelf-Evolving in the Wild:Over the course of ~35 hours of continuous autonomous execution, the model performed 432 kernel evaluations across 1,158 tool calls. It wrote, compiled, profiled, and iterati
Self-Evolving in the Wild:Over the course of ~35 hours of continuous autonomous execution, the model performed 432 kernel evaluations across 1,158 tool calls. It wrote, compiled, profiled, and iteratively improved the Extend Attention Kernel entirely on its own — 10.0x geometric https://t.co/zn4mqAnPPc
View originalCross-Harness Generalization:Across QwenClawBench and CoWorkBench, Qwen3.7-Max delivers strong, consistent performance regardless of the harness used at evaluation time, confirming that the model has
Cross-Harness Generalization:Across QwenClawBench and CoWorkBench, Qwen3.7-Max delivers strong, consistent performance regardless of the harness used at evaluation time, confirming that the model has learned to solve tasks — not to exploit particular harnesses. https://t.co/aSZaOLTEbU
View originalAgent Scaling:Building on Qwen3.5's environment scaling approach, we've aggressively expanded the quality and diversity of agentic training environments in Qwen3.7 — agentic capabilities generalize fr
Agent Scaling:Building on Qwen3.5's environment scaling approach, we've aggressively expanded the quality and diversity of agentic training environments in Qwen3.7 — agentic capabilities generalize from diverse environments, just as language models do from diverse text. The https://t.co/s2ZbpIERZf
View originalPerformance:Qwen3.7-Max performs strongly across benchmarks in coding agents , and improves massively in general-purpose agents. Qwen3.7-Max also demonstrates exceptional strength on the hardest reaso
Performance:Qwen3.7-Max performs strongly across benchmarks in coding agents , and improves massively in general-purpose agents. Qwen3.7-Max also demonstrates exceptional strength on the hardest reasoning benchmarks, and stands out in general capabilities and multilingualism. https://t.co/dwtyxs05f1
View original📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑💻 Coding agent, end to end. Frontend prototypes, multi-file refa
📣Meet Qwen3.7-Max — our latest flagship, made for the Agent Era. A versatile foundation for agents that actually get things done: 🧑💻 Coding agent, end to end. Frontend prototypes, multi-file refactors, real debugging — nails it. 🗂️ A reliable office and productivity assistant. https://t.co/IsgHAoWKV5
View original🚀🚀Qwen3.7 Preview lands on Arena ! Here come Qwen3.7-Max-Preview & Qwen3.7-Plus-Preview. Alibaba now #6 lab in Text, #5 in Vision.⚡️⚡️ Can't wait to release Qwen3.7 series models!Stay tuned!
🚀🚀Qwen3.7 Preview lands on Arena ! Here come Qwen3.7-Max-Preview & Qwen3.7-Plus-Preview. Alibaba now #6 lab in Text, #5 in Vision.⚡️⚡️ Can't wait to release Qwen3.7 series models!Stay tuned! @arena
View original🚀Qwen3.6-Plus is on Nous Portal now and FREE for a limited time. Hermes Agent, here we go!! ⚡️ @NousResearch
🚀Qwen3.6-Plus is on Nous Portal now and FREE for a limited time. Hermes Agent, here we go!! ⚡️ @NousResearch
View original📣We're calling for ambassadors! Whether you're a developer with great technical taste or a local community leader who loves bringing people together, we'd love to have you join us. Visit the websit
📣We're calling for ambassadors! Whether you're a developer with great technical taste or a local community leader who loves bringing people together, we'd love to have you join us. Visit the website below for more details and to apply. In return, ambassadors will receive early https://t.co/BvowB4fUii
View originalRepository Audit Available
Deep analysis of QwenLM/Qwen — architecture, costs, security, dependencies & more
Alibaba Qwen uses a tiered pricing model. Visit their website for current pricing details.
Key features include: Large language model capabilities, Multimodal model support, High scalability for enterprise applications, Customizable training options, User-friendly API for integration, Advanced natural language understanding, Real-time data processing, Support for multiple languages.
Alibaba Qwen is commonly used for: Content generation for marketing, Customer support automation, Data analysis and insights extraction, Personalized learning experiences, Chatbot development for various industries, Creative writing assistance.
Alibaba Qwen integrates with: Slack for team collaboration, Zapier for workflow automation, Google Cloud for scalable deployment, Microsoft Teams for communication, Jira for project management, Salesforce for CRM integration, Shopify for e-commerce solutions, WordPress for content management.
Alibaba Qwen has a public GitHub repository with 20,881 stars.
Based on 97 social mentions analyzed, 14% of sentiment is positive, 86% neutral, and 0% negative.