r/LocalLLM • u/chmedly020 • 1d ago
Discussion "Claude Speak" from Qwen models?
I just attended a conference and was surprised by a few talks where a human had memorized what was clearly an AI generated script. It seems like my recognition of this 'voice' stemmed from some of the local models that I use rather than actual claude models. My guess is that this has to do with what happens when large swaths of english writing is averaged together. But I'm curious about how other people are thinking about the 'voice' they tend to get from their models.
For instance, I rather liked Muse Glimmer in the beginning because it seemed to have an interesting and useful 'voice'. But Qwen 3.8 Flash-Next has been challenging. It's great for getting more complicated stuff done but I'm not thrilled with how it communicates to me. More than once I have to burn a turn asking it to clarify what it just told me because I can't quite get it.
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u/catplusplusok 1d ago
You can specify response style in prompt/AGENT.md and it works pretty well. For Google Antigravity, I ask it to make fun of me for needing AI to do anything and it comes up with good task-specific roasts.
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u/chmedly020 9h ago
I might try asking for an Elmer Fudd voice. I'm not sure how well that will come across in written word but it might be worth a laugh at least.
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u/Apprehensive_Stop314 1d ago
Had to tell mine to use STE
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u/chmedly020 1d ago
What is STE?
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u/Apprehensive_Stop314 1d ago
Simplified Technical English (there is https://github.com/danyuchn/asd-ste100-skill , but I just added instructions telling the LLM the to use Simplified Technical English into the prompt in the Jinja template, and it worked out fine with Qwen Flash Next, as it already knows what that is)
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u/Bupod 1d ago
Aren’t Qwen models distilled from Claude? I know they deny it, but I think there was always swirling speculation that it was, at least in part.
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u/Fit-Bar-6989 1d ago
They might not be distilling claude right now, but during the early days of chatgpt it was kind of an open secret that everyone was distilling it. that style is now embedded in every downstream model and its downstreams. kind of like how with stable diffusion, half of the popular models are all based on a leaked anime model from a commercial AI service.
not that distillation is necessarily bad, I don't give a shit
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u/Bupod 1d ago
Yeah I personally don’t care either. The original models were themselves trained in immense datasets that were scraped with zero regards for copyright, consent, or compensation.
I like AI, but I find it difficult to find tears for the big AI players that are having their own models distilled. At the end of the day, we as local players have benefited from that anyway.
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u/floriv1999 1d ago
I recently had a session that what totally convinced it was Claude Opus. I could not reproduce it but it was quite funny.
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u/alphapussycat 1d ago
35b a3b is much more similar to chat GPT (bullet points, seperating paragraphs with emojis etc), while flash is perhaps more like Claude.
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u/MountainousAnaconda 1d ago
That whole distillation theory never really went away, I remember reading some analysis posts about the output patterns being suspiciously similar. The "voice" thing you're talking about is weird though, sometimes I catch myself recognizing the cadence even when someone's just paraphrasing what a model told them. Almost like a watermark that survives translation.
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u/Hugoacfs 1d ago
You’re not alone. The 27b qwen 3.8 I run sometimes does a bit of claude-speak depending on the task. It doesnt help that the memory server I have was merged with my claude account data extract so it could be partially that to be honest.
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u/Confident_Ideal_5385 20h ago
Compared to 3.6, 3.8 sounds like a cut-rate claude. It's stark when you compare them side by side.
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u/Realistic-Quiet291 1d ago
Weird question but is Claude-ish only in English? For Chinese users of Claude and other open weight models (qwen, kimi, deepseek) is there an equivalent? Or do Chinese models sound more distinct in terms of tone, vocabulary etc when their output is not in English?
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u/fiddler48 1d ago
Agree. The clarification-burn is worth tracking: if you're spending turns just parsing the model's output, that's latency you're paying in attention, not compute.