Alibaba says its 2.4T-parameter Qwen3.8-Max tops Moonshot's Kimi K3 on some benchmarks and it plans to release Qwen3.8-Max's and Qwen3.8-27B's weights next week

Alibaba Group Holding Ltd. released its latest flagship AI model, with performance claims putting it alongside global leaders like Anthropic's Fable.

Bloomberg 2026-08-03 Luz Ding

Context & Ripple Effects

Alibaba had already positioned Qwen3.8-Max as a frontier-model preview with an eventual open-weight release, following its July Qwen3.8-Max preview. This report turns that stated direction into a near-term distribution step for both the flagship and a smaller 27B model.

The move extends Alibaba’s prior open-weight strategy: Qwen3.5 was released as an open-weight multimodal model, while the earlier Qwen3-Max-Preview was not open source. On the same day, Alibaba also set Qwen3.8-Max API prices below Kimi K3’s, making performance and access part of the same competitive pitch.

First-order effects

Alibaba can put Qwen3.8-Max and Qwen3.8-27B into developers’ hands beyond its hosted API once the planned weight release occurs, while using claimed benchmark results to market the models against Kimi K3 and Anthropic’s Fable.
Moonshot faces a more direct comparison point in Kimi K3: Alibaba is pairing claims of stronger results on some benchmarks with lower reported API pricing.

Second-order effects

Enterprise and developer buyers gain more leverage to compare hosted access against deploying an open-weight alternative, shifting evaluation toward workload-specific performance, operating cost, and control rather than benchmark rank alone.
Rival model vendors may face pressure to respond through model updates, pricing, or distribution terms as Alibaba combines a flagship release with a smaller model and planned weights.

Third-order effects

If frontier-capable models increasingly arrive with accessible weights, differentiation may move away from merely possessing a top benchmark model toward deployment tooling, cloud integration, and the cost of useful production work.
This is another step in an AI procurement market where buyers can mix proprietary APIs with self-hosted or customized models; the durable winner will depend on real-world performance and operating economics, not vendor claims alone.

The trend: The story fits the shift from frontier-model announcements toward competition over buyer choice, cost, and distribution across open-weight and hosted AI offerings.

Discussion

@kimmonismus @kimmonismus on x
Holy, China strikes again: Qwen3.8-Max reportedly worked autonomously for 16 days …
@alibaba_qwen @alibaba_qwen on x
📢Meet Qwen3.8-Max — our most capable model to date. Next week, the open weights …
@chamath Chamath Palihapitiya on x
Very impressive.
@arena @arena on x
Big news: Qwen3.8-Max by @Alibaba_Qwen just landed at #4 on the Frontend Code Arena leaderboard with a score of 1,668! …
@igornefedovi Igor Nefedov on x
Can't wait to run Qwen3.8-27B locally. Current setup: dual RTX 3090s, Threadripper PRO 9955WX, WRX90E, and 64GB RAM. A Mac mini runs the agent that controls the workstation. Benchmarks soon [image]
@andrew_n_carr Andrew Carr on x
This model just broke the harnessmaxximg approach of the closed labs. By mixing in harnesses as part of the unified reward suite, the new 2T+ Qwen model generalizes across harnesses! [image]
@dtcb Cole Brown on x
@AndrewCurran_ I used the preview model while they were polishing it up. It was quite fast, owing to the linear attention and sparsity. It was definitely not competitive with K3 in my experience. Much less thorough. Wouldn't rely on it. Still a big Qwen fan, but figured I'd share…
@natolambert Nathan Lambert on x
Here we go, another week another frontier open weight model.
@yacinemtb Kache on x
And just like that Commoditized
@jason @jason on x
Not only is China making increasingly competitive models, they're also making world-positive AI marketing! 😂😂😂 THE COMPUTERS ARE GOING TO DO OUR JOBS FOR US AND WERE ALL GOING TO THE BEACH! 🏖️
@0xsero @0xsero on x
Rejoice! Qwen3.8-27B is coming out next week and it'll be open weights!
@healthranger @healthranger on x
Oh, this is gonna be good. Qwen's 27B model is their best one yet, at least for everyday workloads. In version 3.8, it's going to be amazing. With Unsloth making it run on GPUs under 20 GB, this is going to put it well within reach of a LOT of everyday users.
@alibabagroup @alibabagroup on x
Introducing Qwen3.8-Max, the largest and most capable flagship model to date! With 2.4 trillion parameters and a 1 million-token context window, it is designed for advanced coding, real-world tasks, in-depth research, and tackling long-horizon challenges. #AlibabaAI #Qwen
@cgtwts @cgtwts on x
“Sir, a new open-source model just dropped. It is 2.5x cheaper on input, 4.2x cheaper on output and almost matches Claude Opus 5”. [image]
@teortaxestex @teortaxestex on x
Ok these are pretty good scores ...though some crucial agentic ones (NL2Repo, DeepSWE, Agent's Last Exam, AutomationBench) are surprisingly close to the new V4-Flash. But it has vision and it's a big boy. Also, for the first time ever, we'll see @htihle test Qwen-Max. interesting…
@xiong_hui_chen @xiong_hui_chen on x
Excited to share our latest work at Qwen — Qwen3.8-Max! Open weights are coming next week, together with Qwen3.8-27B. More to come 👀
@rastrapalamoab @rastrapalamoab on x
@scaling01 This is what Gemini 3.5 Pro was supposed to be like if it was released on time 2 months ago
@suchenzang Susan Zhang on x
probed it with a math question: seems to have the formatting style of sol and the reasoning laziness of opus, but the weights are dropping next week so i'm definitely not complaining
@morganlinton Morgan on x
Okay, this time I can't deny it, big win for local AI. This could be the first model I actually use for daily coding, running 100% locally.
@yuchenj_uw Yuchen Jin on x
Qwen3.8-Max is going open-weight next week. It marks the first time Qwen will open-source the weights of a Qwen-Max-class model. The second >2T open-weight model after Kimi K3, the benchmark results look amazing, hopefully it's MIT license. Let's go oss LLMs!
@gelassoldat Ryan on x
@UnslothAI Can we squeeze this in GPU models with 16g vram? Would love to see that.
@unslothai @unslothai on x
Qwen3.8-27B is coming! 🔥 Will run locally on 17GB RAM/VRAM setups.
@mrahmadawais Ahmad Awais on x
@AlibabaGroup thank you for deciding to open source it. we shipped it in @CommandCodeAI and this is one of the few models that solved all our internal benchmark hard questions on 3x runs. excited to see 27B and hopefully 35B version as well.
@cline @cline on x
Qwen3.8-Max is Alibaba's largest model yet at 2.4T params, and shows a 2% higher benchmark result on Terminal-Bench than Fable 5. This comes just days after DeepSeek V4-Flash claims similar performance. Open weights have surpassed closed models.
@scaling01 @scaling01 on x
Qwen3.8-Max is now available and weights will be released next week it's a 2.4T@95B MoE model, and Qwen currently serves it almost 3x cheaper than Kimi-K3 not sure why they didn't compare it to Kimi-K3 and Opus-5
@andrewcurran_ Andrew Curran on x
The new Qwen is here, and it is very strong. Open weights will be released next week. [image]
@kylehessling1 Kyle Hessling on x
New Qwen 3.8 27B confirmed soon! @Alibaba_Qwen is currently carrying the entire open source AI scene …
@theahmadosman Ahmad on x
Looks like we will be getting the weights of Qwen3.8-Max and Qwen3.8-27B next week We are eating GOOOOD boys
@skiipy88 @skiipy88 on x
@scaling01 Let's be honest, 3.8 27B is the real headline
@chahatusharma Chahat Sharma on x
Brother the “hopefully MIT” is doing a LOT of work there. Qwen's open releases have run Apache 2.0, and a Max class model is exactly where a company starts bolting on usage restrictions. Until the license file is actually up next week this is an announcement, not an open weight m…
@matviy_ch Matviy on x
@yacineMTB Anthropic gets decimated with their prices. Biggest beating in AI history. How many billions in valuation will they lose before an IPO? @Polymarket guy, you have to make the odds for that.
@genai_is_real Chayenne Zhao on x
Congrats to the Qwen team! The recent wave of model releases across the ecosystem …
@vsaietta @vsaietta on x
@Yuchenj_UW even with a clean license, a 2T+ param model isn't something most people can run locally anyway, that gate is hardware not legal text. open weights at this size mostly help labs that already have the GPUs to serve it, not individual devs on a single box.
@shuai_bai_ Shuai Bai on x
One of the things we are most excited about in Qwen3.8-Max is its multimodal intelligence. …
@jun_song Jun Song on x
Another frontier AI dropped from Qwen. They are saying Qwen3.8-27B is coming. That's the most interesting part.
@morganlinton Morgan on x
Sunday nights are now for model drops.
@lottolabs @lottolabs on x
Bros they did it the madmen did it Qwen 27b 3.8 is here
@timkellogg.me Mr. Tim on bluesky
Qwen3.8-Max: a 2.4T soon-to-be-open beast of a model that truly rivals Fable and Sol — qwen.ai/blog?id=qwen... [image]
@sungkim Sung Kim on bluesky
Alibaba's Qwen3.8-Max (open-weight next week) — A 2.4T MoE with 95B active. — 📖 Blog: qwen.ai/blog?id=qwen3.8 — ✅ Qwen Studio: chat.qwen.ai?models=qwen3... ⚡ API: www.qwencloud.com/models/qwen3... Qwen Code: github.com/qwen-code-de... [image]
@cjonesny.com Chris Jones on bluesky
Imagine trying to vaguely parse this even 5 years ago. [embedded post]
@isolyth.dev Eris on bluesky
qwen.ai/blog?id=qwen... Qwen 3.8 max is now available via API and open weight (along with a new qwen 27b!!!!!!!!!! 🫪🫪🫪🫪) next week! It seems to match or beat O4.8 on many benches and surpasses or matches Fable on a few. I'm mainly just excited for Qwen3.8-27B [image]
r/unsloth r on reddit
Kindly Benchmark Higher Quants of DeepSeek-v4-flash Against Qwen-3.6-27B Q8!
r/singularity r on reddit
Qwen 3.8 max benchmarks
r/LocalLLM r on reddit
Qwen 3.8 27B coming next week! woo hoo!
r/codex r on reddit
reset incoming in 3... 2...
r/LocalLLaMA r on reddit
Qwen3.8-27B announced alongside Qwen3.8-Max
@arena @arena on x
Qwen3.8-Max by @Alibaba_Qwen has reshaped the cost-performance Pareto frontier in Frontend Code Arena, with pricing of $2 per input MToken and $6 per output MToken. Top models on the Pareto frontier: - Claude-Opus-5 - Kimi-K3 - Qwen3.8-Max - GLM-5.2 - DeepSeek-V4-Flash Congrats t…
@bookwormengr @bookwormengr on x
Where is Alibaba running Qwen-3.8-Max? — What is noteworthy with this release …
@jaminball Jamin Ball on x
New open weight model is out - Qwen 3.8 Max. Here's how the “vanilla” pricing compares between …
@jenzhuscott Jen Zhu on x
All the ads from Chinese labs are pro-human life. No AI gonna wipe out everyone's job. No AI escaping fear marketing. Just better life to enjoy and chill because of AI. I can live with these messages.
r/FPGA r on reddit
Qwen3.8-Max release highlights SystemVerilog development 👀

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