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Is Qwen 4 Being Tested on Arena AI? What We Know About Its Release

Author
Viner Shakirov
Oct 23, 2026, 08:29 UTC
Reading time: 10 min
News & releases
Is Qwen 4 Being Tested on Arena AI? What We Know About Its Release

Alibaba has said very little about Qwen 4 so far, so rumors keep multiplying around the model. This week two new ones appeared: video comparisons that supposedly show tests of Qwen 4 (on Arena AI under the codename Kalmia) and Kimi K3.1, and a ranking screenshot with a very high Qwen 4 score. All that is officially known is that Alibaba has described Qwen 4 as "in training."

We'll go through what in all this is confirmed and what isn't, and what users want from the new model. Let's start with the videos.

Where Things Stand

The author of the LuminaBench channel on X posted a one-minute clip, "Kimi K3.1 vs Qwen 4: 3D helicopter." According to the author, both models got the same prompt: build a 3D helicopter with takeoff, landing, assembly by parts and an exploded view. Generation took 15-20 minutes for each. It looks very good, but it is not yet known for certain whether these really are the new Qwen and Kimi models.

Source of the video: @LuminaBench on X, October 22, 2026.

The same author also posted a second clip: a drone racing game in which Qwen 4 (labeled Kalmia on the video) is compared with GPT-6.1 Sol on Max. He says he enjoyed playing the Qwen 4 version more, but the Sol game looks better and more polished. For scale, he calls Sol a quite strong model with 52 points on the Artificial Analysis index. That matches the site's table: GPT-6.1 Sol on max has 52 there.

Source of the video: @LuminaBench on X, October 22, 2026.

What can and can't be taken from this:

  • Each clip is one prompt and one attempt per model. A test like that can't tell you which model is better overall.
  • In the helicopter clip, generation took 15-20 minutes. That is an agentic task, not an ordinary chat: the model spends a long time writing and re-checking code. Such a test says nothing about reply speed in a regular chat.
  • The tweet doesn't say how the author got access to the models. The names "Qwen 4" and "Kimi K3.1" are his claim. Arena.ai later wrote that a new Kimi model is coming but did not name the version; for Qwen 4 there is no confirmation.

What Is Officially Known About Qwen 4

Alibaba mentioned Qwen 4 at the Apsara conference in September. The Alibaba Group press release of September 25 says the next-generation model, Qwen 4, is currently in training. It also mentions the Qwen 4.5 and Qwen 5 lines, which are planned to grow to 5-10 trillion parameters.

The release gives no release date, sizes or license. According to the Japanese site ai-jitan-hub, a slide at the conference read "Qwen4 Series Coming Soon" and listed four variants: Max, Flash, Plus and 27B. The official release does not name the variants.

For now, Qwen 3.8 is what is available on the site and in the API: Qwen 3.8 Max and Qwen 3.8 Flash. We covered what is new in them in the Qwen 3.8 overview.

What About Kimi K3.1

The second participant in the same clip is Kimi K3.1. Moonshot AI has not officially announced such a model; its current one is Kimi K3 (released in July 2026, see our Kimi K3 breakdown). The first signal about K3.1 is a mention in Kimi Code that the same LuminaBench noticed on October 21; the outlet RuntimeWire called it a "prelaunch clue, not a product announcement," that is, a hint rather than an announcement.

The second signal came on October 23: Arena.ai wrote on X that a new Kimi model is coming and promised to show where it lands in the Arena ranking ("A new model from @Kimi_Moonshot is coming. Stay tuned for where it lands in the Arena"). The tweet names neither a version nor a date, so it only confirms that a new Moonshot model will soon appear on Arena, not that it is K3.1. There is no such message from Arena about Qwen 4. We will write about K3.1 separately once there is confirmed data.

How Models Appear on Arena and How Far to Trust It

Arena (formerly LMArena) says itself that it works with vendors who give the community pre-release versions. In battle mode, models may appear under codenames and aliases, and the name is revealed after voting. According to Arena itself, over two years it has had more than 300 pre-release tests and more than 400 public models.

But a codename guarantees nothing. A model's result goes into the public ranking only after release and under its official name, and some of the tested variants never reach the public at all. So "a model that looks like Qwen has been spotted on Arena" is an early signal, not a release date.

Where to Be Careful

News about upcoming model releases is a field for speculation. For example, a screenshot is going around the internet in which a preview of Qwen 4 Max supposedly scores 53 points on the Intelligence Index at Artificial Analysis. For scale: Qwen 3.8 Max (0902), released on September 2, scores 45 points on the Artificial Analysis site and sits 33rd out of 214. A jump of 8 points would be very noticeable.

I checked the Artificial Analysis site and found no confirmation of this information: Qwen 4 is not in the ranking, and the best result among Qwen models is those same 45 points for Qwen 3.8 Max. Participants of r/Qwen_AI didn't find such an entry either and call the picture a fake, while the author of the post in r/LocalLLaMA himself calls it an assumption. So the number 53 should be read as a rumor.

What the Community Says

r/LocalLLaMA has almost 250 comments. The author of the post is sure that the model with the codename kalmia has a "fingerprint" matching Qwen, but calls it a guess. r/Qwen_AI has 124 comments and noticeably more skepticism: the post is called "slop," and the release date in the post itself reads "at the end of the month, in November and in other months." That is not a date. Another commenter names October 29, but nobody answered the question "source?" in the thread.

What People Would Like to See in Qwen 4

Qwen models are very popular among enthusiasts and fans of running neural networks locally on their own computers. They are arguably among the most popular local LLMs right now, so the community has high expectations for new releases. Here I tried to collect the key points from the comments. These are users' wishes, not Alibaba's plans:

Small models. Many ask for a "small Qwen 4": a 27B version, as well as 9B, 4B for weak computers, and a 35B MoE with 3B active parameters. The author of the post thinks 27B will be the smallest, and several commenters say a 35B MoE will not come out at all. There is no confirmation.

A Flash of the same size. Equally popular is the wish that Qwen 4 Flash not grow compared with Qwen 3.8 Flash Next. The example people fear is Flash from DeepSeek V4.1: by one commenter's count, it grew from 284B to 552B parameters. People run Flash Next at home: one writes about 30-35 tokens per second on a PC with 32 GB of RAM and a 4070 Super graphics card, another about 50-70 tokens per second on a Mac M4 Max with 128 GB. These are messages from the discussion, not measurements.

Part of the weights on disk. Users praise an approach where a large n-gram table (called an engram in the discussion) sits on an SSD and doesn't take up video memory. They ask for a 27B with such a table, or a MoE of about 50B with 5B active parameters and a 100B table.

Lower memory requirements. People ask for a KV cache (memory for context) half the size for 27B, even if the tests come out slightly worse, and for quantization-aware training (QAT), as with Gemma 4, so that a 4-bit version loses less quality. They also ask for a model for 24 GB graphics cards and note a shortage of models in the 120-200B range.

Readable answers. The main complaint about Flash Next is its writing. One user asked for an implementation plan and got a "dump of the agent's inner thoughts" in telegraphic bullet points. Another hands text tasks to a Gemma subagent. People ask for plain language, less looping in 27B's reasoning, better instruction following and clarifying questions, fewer Chinese characters in answers and better multilingual ability.

Fewer made-up facts. One user writes that the previous 35B MoE invented references when working with knowledge tasks, so agents had to redo the work.

Open weights and honest tests. People want open weights for Flash and Plus and don't expect them for Max: according to a commenter, Alibaba's flagship is rarely published. They ask that the model not be "tuned for benchmarks," that it be faster, and that it have computer use.

What This Means for You

If the rumors turn out to be true, we will see a new Qwen generation in several variants at once: if the conference slide is right, Max, Flash, Plus and 27B. Those who run models themselves will have to look at the size and memory requirements of Flash and 27B, and everyone else at price and quality through the API. At the same time, don't rely on the screenshot with the score of 53: it is most likely fake. Real scores, prices and sizes will become known only after the official release.

If you are choosing a model now, go with what has already been released. GPTunneL prices, $ per 1K tokens, input / output:

ModelContextPrice, $ per 1K
Qwen 3.8 Max1M0.004 / 0.012
Qwen 3.8 Flash1M0.0003 / 0.00095
Kimi K31M0.006 / 0.03

When Qwen 4 is officially released, we will update this article: we'll add prices, benchmarks and a comparison with the current versions.

Where to Try

Qwen 3.8 and Kimi K3 work on GPTunneL from one balance, with no VPN needed and no separate subscriptions: you can compare them on your own task and then decide whether to move to the new versions.

Sources