Every week, I organize 400 to 700 links into roughly 60 categories as part of my ongoing effort to learn about AI. This is my personal notebook, which I enjoy sharing with friends… a hobby and a labor of love, rather than a commercial publication or product.
If you arrived here through a search or shared link, this page collects the links I found for Alibaba for the week ending September 4, 2026.
As part of my learning process, I like to automate the category covers. It gives me a chance to learn Python and APIs.
This week’s cover prompt was written using Claude Opus 4.7, and the image was generated using Nano Banana 2.1.
Category Cover Image Prompt: A vertical psychedelic screen-printed gig poster of a serpentine Eastern dragon spiraling upward with scales blooming into glowing paper lanterns and swirling op-art smoke, clutching a shimmering orb etched with a stylized Q, framed by autumn leaves and a harvest moon in an ornate border, with the words 'Alibaba' hand-lettered in bold Fillmore-era psychedelic title text arching across the top. Flat ink layers in electric magenta, acid orange, deep teal, and lime green on cream paper stock with slight registration offset and visible paper texture.
This Week in Alibaba News
Summary by Claude Sonnet 5.5 based on this week’s links:
- Qwen3.8-Max-0902 takes the WebDev lead: Alibaba's upgraded Max model, listed at 2.4T parameters and 1M context, debuted at #1 on Arena's Code Arena WebDev board with 1691 points. Arena said that is 3 points above Claude Opus 5 (Max) and priced at a blended $5 per million tokens.
- Flash-Next gets mixed field reports: Arena placed Qwen3.8-Flash-Next at #24 overall and #7 among open models across 8.7K+ agentic sessions. Eric Hartford (QuixiAI) countered that, at FP8, it lost track of a multi-turn conversation and answered a question from two turns earlier.
- Wan 3.0 leads video editing: Alibaba's Wan 3.0 debuted at #1 on both the Artificial Analysis Video Editing leaderboard and Arena's Video Edit Arena, where it leads dreamina-seedance-2.5 by 4 points. It was a close #2 in text-to-video with audio on Artificial Analysis.
This summary was generated by Claude Sonnet 5.5 to help you explore the links below. Rest assured, I select, organize, and check the links by hand in Google Sheets, and write the introduction and personal commentary in The Main Newsletters myself each week as a labor of love.
This week's links related to Alibaba
Qwen3.8-Flash-Next by @Alibaba_Qwen has landed in Agent Arena, ranking #7 among open models (#24 overall) with +2.4% net improvement across 8.7K+ real-world agentic sessions! Among open models, it sits just behind DeepSeek V4 Flash (High) at #6 (+3% net improvement) and two
https://x.com/arena/status/2094566204488962483
🏆 #1 on CodeArena: WebDev leaderboard. Qwen3.8-Max-0902 jumps from 1669 to 1691, setting a new record for agentic coding (WebDev) workflows, with standout strength in multistep reasoning, tool use, and full app generation. Thanks for the recognition! @arena
https://x.com/Alibaba_Qwen/status/2094976556494209206
Banger paper from the Qwen team. If you evaluate agents on anything longer than a single session, this one is worth your time. (bookmark it) E-Commerce Bench runs an agent through a simulated 365-day year operating several online stores at once. 18 frontier models are scored
https://x.com/dair_ai/status/2094872928240447665
Hermes now has a local backend! There’s support for Unsloth UD-Q4_K_XL and UD-Q4_K_M quants for DeepSeek-V4-Flash, Qwen3.8-27B, 3.6-35B-A3B and Qwen3.8-Flash-Next in Hermes!
https://x.com/danielhanchen/status/2095623899979600152
If you build agent skills in production, check out this great paper from Alibaba. You can think of a production agent skill as a directory. The root loads on activation, and references, schemas, scripts, assets and nested subskills load only when an execution path reaches them.
https://x.com/dair_ai/status/2094811526767182090
Big news: Qwen3.8-Max-0902 by @Alibaba_Qwen just debuted at #1 overall in the Code Arena: WebDev with 1691 pts! It scores 3 pts above Claude Opus 5 (Max), 17 pts above Kimi K3 (Max), and 22 pts above the previous Qwen3.8-Max. Priced at a blended $5/MToken, Qwen3.8-Max-0902 also
https://x.com/arena/status/2094974637704913198
Wan 3.0 debuts at #1 on the Artificial Analysis Video Editing Leaderboard, and is a close #2 in Text to Video with Audio Wan 3.0 is Alibaba’s new all-in-one video generation and editing model, positioned as a single system for turning multimodal creative direction into video. It
https://x.com/ArtificialAnlys/status/2095349174799888760
Exciting news: Wan 3.0 by @Alibaba_Wan has claimed the #1 spot in the Video Edit Arena! With 1414 ps, Wan 3.0 leads dreamina-seedance-2.5 by 4 pts and MiniMax-H3 by 22 pts. This release marks @Alibaba_Wan’s debut in the Video Edit Arena. This newer Arena now features 10 models
https://x.com/arena/status/2093143153167810608
Qwen3.8-Flash-Next is #24 overall with +2.4% net improvement (#7 among open), and by signal: – Confirmed Success: +12.3% – Bash Recovery: +2.9% – Praise vs. Complaint: -1.6% – Steerability: -1.1% – No issues with Tool Hallucination
https://x.com/arena/status/2094566207794061800
🚀Qwen3.8-Max just got upgraded. Meet Qwen3.8-Max-0902! 2.4T parameters. 1M context tokens. Built for real world complexity. Further post trained on Coding & Cowork, Qwen3.8-Max-0902 now delivers stronger performance across complex enterprise tasks, scientific research, and
https://x.com/Alibaba_Qwen/status/2094968708288680276
LESSON LEARNED: Always use BF16 kv cache. I was using turboquant. Yeah the VRAM consumption sucks – so another trick is to CPU Offload the kv cache. Implemented in SlimServe for 3090 and Qwen (it requires extensive testing to get it right) I have further work to universalize
https://x.com/QuixiAI/status/2093405502181179422
125B/6B, 1M context, multimodal, now in OpenCode Go. ⚡ Happy coding with Qwen3.8-Flash!
https://x.com/Alibaba_Qwen/status/2093227357951897687
My experience with Qwen3.8-Flash-Next is that it can’t even keep track of a multi-turn conversation. It answers questions I asked 2 turns ago. This is at FP8
https://x.com/QuixiAI/status/2093175458569326919
Qwen3.8 Flash is the third Qwen3.8 release, after Max and 27B it uses a 125B MoE architecture with only ~6B parameters active per token Flash is ~20x cheaper and ~2x faster than Qwen3.8 Max, often delivering performance close to Max hosted version comes with a 1M token context
https://x.com/skalskip92/status/2093384847649571325
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