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Qwen3-Omni-Flash-2025-12-01：a next-generation native multimodal large model

(qwen.ai)
314 points pretext | 1 comments | 10 Dec 25 16:13 UTC | HN request time: 0.194s | source
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gardnr ◴[10 Dec 25 17:37 UTC] No.46220742[source]▶
This is a 30B parameter MoE with 3B active parameters and is the successor to their previous 7B omni model. [1]

You can expect this model to have similar performance to the non-omni version. [2]

There aren't many open-weights omni models so I consider this a big deal. I would use this model to replace the keyboard and monitor in an application while doing the heavy lifting with other tech behind the scenes. There is also a reasoning version, which might be a bit amusing in an interactive voice chat if it pronounces the thinking tokens while working through to a final answer.

1. https://huggingface.co/Qwen/Qwen2.5-Omni-7B

2. https://artificialanalysis.ai/models/qwen3-30b-a3b-instruct

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andy_xor_andrew ◴[10 Dec 25 18:37 UTC] No.46221587[source]▶
> This is a 30B parameter MoE with 3B active parameters

Where are you finding that info? Not saying you're wrong; just saying that I didn't see that specified anywhere in the linked page, or on their HF.

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1. plipt ◴[10 Dec 25 19:36 UTC] No.46222506[source]▶
The link[1] at the top of their article to HuggingFace goes to some models named Qwen3-Omni-30B-A3B that were last updated in September. None of them have "Flash" in the name.

The benchmark table shows this Flash model beating their Qwen3-235B-A22B. I dont see how that is possible if it is a 30B-A3B model.

I don't see a mention of a parameter count anywhere in the article. Do you? This may not be an open weights model.

This article feels a bit deceptive

1: https://huggingface.co/collections/Qwen/qwen3-omni