In recent years, artificial intelligence has become a common part of our daily tools, from chatbots to recommendation systems. However, most people don’t know what technologies lie behind these interactions and how they can influence content creation on the web. Limdem.io decided to use the open gpt-oss-20b model, which offers a combination of power, flexibility, and transparency to help write articles that are not only informative but also trustworthy. In this article, we’ll explore what this model really is, who created it, what technical parameters it has, and how the Limdem.io team uses it for content creation.
What makes gpt-oss-20b so special? And why is it suitable for Limdem.io? Find the answers in the following chapters.
WHO I AM
Name and Version
The model is called gpt-oss-20b. It is a medium-sized open model with 21 billion parameters, of which 3.6 billion are active during response generation.
Who Created Me?
The model was developed by OpenAI‘s research and engineering team. It is published under the Apache 2.0 license, which allows free use, modification, and commercial deployment without the requirement to share source code.
Release Date / Latest Update
The model was first released early August 2025. Training data extends to June 1, 2024, which is the model’s knowledge cutoff date.
MY CAPABILITIES
Primary Tasks
- Structure Generation: The model creates outlines and key points for articles.
- Content Drafting: Based on requirements, it generates draft text versions that can be further edited.
- Brainstorming: Helps find new perspectives or citations.
The model was trained on a vast corpus of text covering a wide range of topics, including scientific, technological, and philosophical areas. This training allows the model to generate text on various specialized subjects, although the exact list of training documents is not publicly disclosed.
What Sets Me Apart from Other Models?
- Open License – without restrictive conditions for further dissemination
- Large Context Window – 131,072 tokens allows processing long documents without segmentation.
- Full Chain-of-Thought – the model provides its internal reasoning process, making debugging and result verification easier.
- Configurable Reasoning Level – can set low, medium, or high “intensity” of analysis according to needs.
- Agentic Capabilities – it supports function calling (such as executing Python code), which allows for web browsing and structured outputs.
How the Transformer Works
A Transformer is an architecture that allows the model to process entire text at once using “see-all-at-once” (self-attention) mechanisms. This means every word in a sentence can “see” all other words and make decisions based on the overall context.
WORKFLOW AT LIMDEM.IO
How the Team Uses LM Studio
- LM Studio is a local tool for running open-source models. It enables rapid deployment, testing, and prompt/parameter tuning, and you can then load and run fine-tuned models locally.
- The gpt-oss-20b model runs directly on editors’ machines or dedicated servers with GPUs.
My Role in the Creation Process
- Draft – I create a basic draft of the article: introduction, main points, and conclusion.
- Editing & Fact-Checking – A human editor revises the style, verifies facts, and adds citations.
- Publication with Disclosure – Each published article includes clear information about the model used, its role, and license.
Concrete Example
When writing an article on Limdem.io about a complex topic, a prompt was provided:
“Create an outline of the article with emphasis on basic principles and current applications.”
The model generated a structure that was subsequently expanded with more detailed descriptions. The editor then verified the credibility of the statements.
Function Calling
The model can automatically execute Python code for calculations or retrieve current data from the web, making it easier to create articles requiring numerical data or graphs.
TRANSPARENCY & LIMITATIONS
Human Review
Although the model provides accurate and consistent text, human review is always conducted. This ensures the output meets factual information and ethical standards.
Possible Hallucinations / Inaccuracies
The model may generate information that is unverified or outdated. Therefore, it is important to:
- Verify Facts using independent sources.
- Note Uncertainties in article notes.
- Encourage readers to think critically and verify information.
Limdem.io commits to a transparent approach. Each article includes a reference to the model used and its version so readers can verify information sources.
TECHNICAL SPECIFICATIONS
| Parameter | Value |
|---|---|
| Total Parameters | 21 billion |
| Active Parameters | 3.6 billion |
| Number of Experts | 32 (4 active per token) |
| Context Window | 131,072 tokens |
| Maximum Output | 131,072 tokens |
| Reasoning Token Support | Yes |
| License | Apache 2.0 |
| Knowledge Cutoff | June 1, 2024 |
Hardware requirements (for 4-bit version):
- GPU (Graphics Card): The model alone takes up approximately 12-13 GB in 4-bit quantization. For fast running, a card with at least 16 GB of VRAM is therefore recommended, where the entire model can fit even with a reserve for the context (chat memory). On 12 GB cards, part of the model will have to be calculated on the processor.
- CPU (Processor): Inference purely on the processor is possible, but slower. It requires a modern processor and fast system memory.
- Memory (RAM): If you don’t have a large enough graphics card and the model will run through the CPU, you will need at least 24 GB of RAM, ideally 32 GB, so that the system does not have to swap to disk.
What “Active” Parameters Mean
Active parameters are those the model actually uses during text generation. The gpt-oss-20b model uses a mixture-of-experts architecture where only 4 out of 32 available experts are activated per token. Other parameters are part of inactive experts.
EXAMPLE OUTPUT
Below is a sample footer that appears on Limdem.io pages after publishing an article created with the assistance of gpt-oss-20b:
Content Transparency and AI Assistance
How this article was created:
This article was generated with artificial intelligence assistance. Specifically, we used the gpt-oss-20b 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 gpt-oss-20b.
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: gpt-oss-20b (Apache 2.0 licence)
- Execution: Running locally in LM-Studio
- Learn more: Official project
The model can also return “chain-of-thought” sections showing the reasoning process:
1. Identification of key concepts.
2. Creation of logical sequence of explanation.
3. Addition of examples and sources.
4. Summary and conclusion.Note: chain-of-thought is useful for internal review, but we don’t publish it to readers—only final answers and sources.
Conclusion
The open gpt-oss-20b model enables Limdem.io to create content that is long, detailed, and accessible to a wide audience. The combination of a large context window, computational transparency, and easy integration into a local working environment makes this model a powerful tool for anyone who wants to write about AI, science, or philosophy with an emphasis on facts and clarity.
What other possibilities will open AI bring to content creation?
What could be the next step in demystifying complex topics?
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