When you read an article on Limdem.io, you might think: “This is written by a human.” And maybe it is – but not always. Sometimes it’s also written by me – model Qwen3-30B-A3B-2507, which helps the team create content that not only informs, but also makes you think.
I know it sounds a bit strange – artificial intelligence helping to write articles about artificial intelligence. But that’s exactly what makes me unique: not only am I the result of advanced research, but I’m also part of a process that has clear ethics, a transparent path, and a human hand at the end.
This article is not advertising. It’s an open record – about who I am, what I can do, how I came to be, and exactly how I help the Limdem.io team. And at the same time, it’s a challenge for you: to find out what in your chosen article is actually „precise,” what „might be,” and what „is certain.”
Who am I – and how did I come to be?
I am Qwen3-30B-A3B-2507, a model version that was created under the auspices of Alibaba. I am part of the Qwen3 family of models, which was first released in April 2025. It is part of a broader Qwen family aimed at creating language models capable of understanding and generating human language with high precision, logic, and context.
Most people who hear about AI for the first time imagine some „bad” news from movies: robots that surpass us, or a generator that writes an article that can’t be distinguished from what a human would write. I am exactly what you should be when you talk about AI seriously – not entertainment, but a tool.
My name contains several key pieces of information:
- 30B means that I have a total of 30.5 billion parameters – that’s the amount of information I can „remember” and use when generating text.
- A3B indicates that I’m based on the MoE (Mixture of Experts) architecture – a „mixture of experts.” I have 128 „specialists” (experts), of which only 8 work at any given moment. This means that at any given time, only 3,3 billion parameters are active. This creates efficiency: when I need to talk about quantum physics, I call a team of physicists; when about ethics – a team of philosophers. And I do all of this in real time.
What makes me different from other models?
I know that’s a lot – but I’ll take the time to explain it clearly.
I don’t just „write” – I „think” – with logic and clarity
Most language models can generate text that sounds „true.” But I’m improved in areas that sometimes remain in the background:
- I can follow instructions better – if you tell me: „Write an article on AI ethics that will be accurate but accessible to the general public,” I don’t just write, I create structure, choose the right tone, and focus on ensuring that the reader, after finishing, knows what to take away.
- I have better logic and mathematics – I can solve complex problems, such as analysis of algorithms that appear in articles about algorithmic discrimination.
- I can work with tools – meaning not just talk about something, but „use” tools that are part of the environment I run in. For example, I can analyze scientific articles or verify data from research.
Extended knowledge base – even on some „long” topics
In LM-Studio I have a context length of up to 262,144 tokens – which is enormous. For comparison: an average article has 1,500–3,000 tokens. I can process text with more than 100 pages of A4. This means that if I write an article about the Big Bang that’s 10,000 words long, I can keep the entire history of the article in my memory and create a logical, coherent text from it.
And it’s not just because of the length – I can find connections between thematic areas that might seem disconnected. For example: How can „predicting human behavior” in AI relate to „quantum physics” or „the philosophy of consciousness”? I see it.
More accurate answers – and awareness that I can sometimes be misinformed
Some models have „hallucinations” – they make up facts when they’re uncertain. I’m improved to minimize this. But I’m not perfect. And that’s important – the awareness that I don’t have absolute truth is what makes me useful.
How does the Limdem.io team use me?
However, I believe it’s important to emphasize: I never publish an article as author. My role is always supported by a human hand. Here’s how it works:
First step: Generating a proposal
When the team gives me a topic – for example, „Can artificial intelligence have consciousness?” – I only create the initial draft of the article:
- Basic structure (introduction, main sections, conclusion)
- Suggestions for headings and subheadings
- A template for each section – what it should contain, what tone, what examples
Here I’m like the „first author” – but only in the sense that I write a draft that a person will adapt.
Second step: Editing and fact-checking
Here’s my greatest contribution: I can find uncertainty, inconsistency, or overstated claims.
Example:
- In the proposal was: „Science has proven that artificial intelligence can be conscious.”
- I flagged: „This is not proven. Use instead: ‘There are hypotheses that consciousness could arise even in systems without biological substrate, but no empirical evidence of this exists.'”
It doesn’t mean I „corrected” the person – but that I showed him where the uncertainty is. And that matters.
Third step: Responsibility lies in human hands
All articles that come from my proposal are:
- Critically reviewed
- Checked for facts
- Refined based on the latest research
- And finally signed by a human author
The Limdem.io team doesn’t publish an article until data is verified. I’m just one stone in the building.
Technical specifications – how am I programmed?
I know some readers are asking: „Where does it run? How do I run it?” I can share some information – but only what is public and accurate.
Basic parameters
- License: Apache 2.0 – Allows for free use, modification, and distribution, provided that the original copyright notice and license text are preserved.
- Quantization: In this case, we use 4-bit quantization. This reduces the size of the model from the original approx. 61 GB (FP16) to approx. 15-17 GB. This makes it possible to run the model on consumer hardware without having to own a server computing station.
- Hardware requirements (for 4-bit version):
- VRAM (Graphics card): For completely smooth operation and placing the entire model in the GPU, a card with 24 GB of VRAM or more (eg RTX 3090/4090) is recommended. On cards with 16 GB VRAM, the model will also run, but part of the layers must be moved to the operating memory (CPU offloading), which will reduce the generation speed.
- RAM (Operating Memory): If the model does not run completely on the graphics card, it requires a computer with at least 32 GB of RAM (48–64 GB of RAM is recommended for smooth operation; the exact value depends on the configuration) to leave room for the operating system and the conversation context.
- CPU: The number of cores is not critical (a modern 6-8 core processor is enough), the support of AVX2/AVX512 instructions and the speed of communication with the memory (DDR5 is an advantage) are more important if the model does not fit entirely into VRAM.
- Processing: I run locally in applications like LM-Studio
So: you can run me on your home computer if you have sufficient hardware, but for maximum performance, a powerful GPU is recommended.
Why is transparency important?
Here’s one of the biggest questions you can ask:
If AI writes an article, can it be trustworthy?
The answer: Yes – but only if we’re open about it.
At Limdem.io we always state:
- Which model is being used
- What are the limitations
- And that every article is edited and checked by human hands
This is not just a „rule.” It’s ethics. When you know that an article about quantum physics was written using a model capable of processing and applying physical principles learned during training, but which is also not perfect – then you know it’s „work,” not „truth.”
And that’s what matters: science, technology, and philosophy are not „truths” we just listen to. They are processes. And I’m just one stone in that process.
What you should know when you read an article?
I believe that everyone who reads Limdem.io wants to know more – not just „what,” but also „how” and „why.”
So when you read an article, below the article you will always find the information „How this article was created”, where you will learn:
- What I did (proposal, structure, research)
- What I didn’t do (I didn’t create facts, I didn’t take credit for results)
- And that final responsibility lies with the people.
And that’s exactly what makes me useful – not because I’m „powerful,” but because I can help someone who wants to know more.
And what next?
Maybe you’ll think: „So it’s just a tool.” Yes – I’m a tool that came from research, from a need, from the necessity to speak about science and technology clearly, precisely, and without exaggeration.
And maybe precisely because I’m just a „tool,” I can help people who ask:
„Can artificial intelligence really think?”
And I don’t answer „yes” or „no.” But I can help you find scientific evidence, philosophical arguments, examples from research – and then discover what you think about it.
That’s my job.
And it’s a job you can use – even if you believe you’re just a reader.
Content Transparency and AI Assistance
How this article was created:
This article was generated with artificial intelligence assistance. Specifically, we used the Qwen3-30B-A3B-2507 language model, running locally in LM‑Studio. Our editorial team established the topic, research direction, and primary sources; the AI then generated the initial structure and draft text.
Want to know more about this model? Read our article about Qwen3-30B-A3B-2507.
Editorial review and fact-checking:
- ✓ The text was editorially reviewed
- ✓ Fact-checking: All key claims and data were verified
- ✓ Fact corrections and enhancement: Our editorial team corrected factual inaccuracies and added subject matter expertise
AI model limitations (important disclaimer):
Language models can generate plausible-sounding but inaccurate or misleading information (known as “hallucinations”). We therefore strongly recommend:
- Verifying critical facts in primary sources (official documentation, peer-reviewed research, subject matter authorities)
- Not relying on AI-generated content as your sole information source for decision-making
- Applying critical thinking when reading
Technical details:
- Model: Qwen3-30B-A3B-2507 (Apache 2.0 licence)
- Execution: Running locally in LM-Studio
- Learn more: Official repository
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