back to top
HomeTechJust After Launching Qwen3.5, Qwen's Core Team Walked Out. Is This the...

Just After Launching Qwen3.5, Qwen’s Core Team Walked Out. Is This the Last Great Qwen Model?

- Advertisement -

Yesterday I was testing Qwen3.5-4B on my machine, genuinely impressed by what a 4B model was doing with images and reasoning. Then I opened X and saw a five word post from Junyang Lin, the man who built Qwen from the ground up: “bye my beloved qwen.”

That was it. No explanation, just a goodbye.

Within hours the replies were flooding in. Developers, researchers, open source contributors all asking the same thing — what just happened? And then Elon Musk’s comment on Qwen3.5 calling it “impressive intelligence density” surfaced, and Lin replied with a simple “thx elon.” People in the comments started connecting the dots — was he already gone when he replied? Did he know? Nobody is quite sure what to make of that exchange but it made the whole thing feel even stranger.

Lin wasn’t alone. Yu Bowen, who led post-training for Qwen, resigned the same day. Hui Binyuan, a core contributor focused on coding, had already left in January. Three of the most important people behind one of the best open source AI model families in the world, gone within months of each other.

I had just tested the model. I had just written about why it was worth your attention. And now the people who built it had walked out.

How Qwen Lost Its Soul

Qwen Team Lead Stepped Down

Lin Junyang wasn’t just a team lead. He had been building Qwen since 2022, turning it from an internal Alibaba project into one of the most downloaded open source model families in the world. Over 400 models released, over a billion downloads. That’s not a department head, that’s the person the whole thing was built around.

His resignation on Wednesday came two days after Qwen3.5 launched with just a five word post on X and silence after that.

Yu Bowen, who ran post-training for Qwen, left the same day. Hui Binyuan, a core contributor focused on coding, had already quietly resigned in January. Three people who understood Qwen at its deepest level, all gone within two months.

What pushed them out isn’t entirely clear. Lin himself said at a Beijing forum in January that his team was stretched thin, spending most of their resources just meeting delivery demands rather than doing the kind of research that actually moves things forward.

Alibaba CEO Eddie Wu responded with a brief statement thanking Lin and announcing a task force to coordinate future AI model development. Reading between the lines that sounds like exactly the kind of corporate restructuring that makes passionate researchers leave separate teams, separate goals, less room to just build something great.

The open source community noticed immediately. Zhipu AI’s CEO was already publicly trying to recruit the departing engineers within hours of Lin’s post.

I tested it right before everything fell apart

The timing is strange to think about. While Lin was probably writing that five word goodbye, I was running Qwen3.5-4B on my machine, genuinely surprised by what it was doing.

Vision works better than you’d expect from a 4B model. I dropped in images and it described them accurately — screenshots, diagrams, general scenes. It stumbled on location and landmark identification occasionally, giving confident answers that were just wrong. But for everyday image understanding it holds up.

Text and reasoning is where it genuinely impressed me. It thinks before it answers, works through problems rather than guessing. For something running on 16GB RAM and 6GB VRAM that’s not what you expect.

The model is good. That’s what makes this whole situation harder to sit with.

What happens to the Qwen models we already have?

The models already out there aren’t going anywhere. They’re open source, already downloaded over a billion times, and the community will keep building on them regardless of what Alibaba does next.

But that’s where the reassurance ends.

The real concern is what comes next. Qwen’s release pace existed because the people behind it genuinely cared. Those people just left. Whether Alibaba keeps the same momentum, or even keeps future models open source, nobody knows right now. A few months ago nobody expected Lin to leave either.

Use it while you can

Maybe Alibaba figures it out. Maybe the new team surprises everyone. But right now the safest thing you can do is download the Qwen3.5 weights locally and keep them. We don’t know if the next version will be this good or this open.

What Lin and his team built was rare, a full open source AI stack, genuinely competitive, freely available. That doesn’t come around often. And right now it feels like we’re watching the end of something without quite knowing what comes next.

Don’t miss any Tech Story

Subscribe To Firethering NewsLetter

You Can Unsubscribe Anytime! Read more in our privacy policy

LEAVE A REPLY

Please enter your comment!
Please enter your name here

YOU MAY ALSO LIKE
Google Built Gemma 4 12B Without Multimodal Encoders

Google Built Gemma 4 12B Without Multimodal Encoders

0
Every multimodal model you've used has the same basic system. Text goes in one way, images go through a vision encoder first, audio goes through an audio encoder first, and then everything gets handed off to the language model in a form it can work with. The encoders are load-bearing and you don't just remove them.Google actually removed them.Gemma 4 12B takes raw image patches and raw audio waveforms and projects them directly into the same embedding space as text tokens. There is no vision encoder or audio encoder. One decoder handling everything.
MiniMax M3 Shows What Happens When AI Stops Thinking in Turns

MiniMax M3 Shows What Happens When AI Stops Thinking in Turns

0
Most models quit around submission 30 because they stop finding improvement and exit on their own. That's what happened when MiniMax ran a CUDA kernel optimization task against a field of frontier models. Every model except two called it done within the first 30 submissions. M3's best result came on submission 145. After 24 hours. After multiple plateaus where the numbers stopped moving and a reasonable model would have concluded there was nothing left to find. That's the thing MiniMax released yesterday. An AI model with a 1M token context window, native multimodality, and apparently a problem with knowing when to stop.
Anthropic Files for an IPO. AI Is Entering Its Public Company Era

Anthropic Files for an IPO. AI Is Entering Its Public Company Era.

0
Anthropic has officially taken its first step toward becoming a public company. In a brief announcement on Monday, the company said it had confidentially submitted a draft S-1 registration statement to the U.S. Securities and Exchange Commission for a proposed initial public offering. The filing doesn't reveal a share price, a fundraising target, or even a timeline. For now, it simply gives Anthropic the option to go public once the SEC review process is complete. Just a few years ago, Anthropic was a small group of former OpenAI researchers trying to build an alternative vision for advanced AI. Today, it sits among the handful of companies shaping the industry's future and that's why this filing matters. It's one of the world's most influential AI labs beginning the transition from a privately funded research company to a business that may eventually answer to public shareholders. For most of the AI boom, the biggest bets were made behind closed doors. Venture firms, sovereign wealth funds, and tech giants supplied the capital while the public watched from the outside. Anthropic's filing suggests that era may be starting to change.