Last Updated on January 8, 2026
Introduction
Private AI for Word has become the primary solution for professionals requiring high-level data security who are increasingly moving away from cloud-based assistants. To achieve a true private Microsoft Copilot alternative, users must deploy a Local LLM directly on their own hardware to eliminate the risks associated with third-party data processing. By running GPTLocalhost as a local Word Add-in, you can deploy this optimized 24B model directly on your hardware. This focus on privacy is a core pillar of our Ultimate Guide to Local LLMs for Microsoft Word.
Watch: Mistral Small 3 Summarization Demo
This demonstration highlights how Mistral Small 3 handles complex document summarization. Watch as it analyzes a long-form document and generates a structured, high-fidelity summary directly inside Microsoft Word without any data leaving the local machine.
For more technical demonstrations of private AI models in Microsoft Word, please visit our channel at @GPTLocalhost.
Technical Profile: Why Mistral Small 3 for Word? (Download Size: 14.33 GB)
Mistral Small 3 is a pre-trained, instruction-tuned model designed to cover the “80%” of generative AI use cases—delivering strong language understanding and instruction-following capabilities. It is a great versatile model for tasks such as long document processing, low-latency applications, and summarization, etc.
- Long-Context Window: Mistral Small 3.1 features a context window of up to 128,000 tokens. This allows it to summarize entire books, lengthy research papers, or complex legal contracts without needing to chunk the text.
- Frontier performance: Achieve closed-source-level results with the transparency and control of open-source models.
- Multilingual: Build applications that understand text and complex logic across 40+ native languages.
- Scalable efficiency: From 3B to 675B parameters, choose the model that fits your needs, from edge devices to enterprise workflows.
Deployment Reminders: Running Mistral Small 3 Locally
When quantized, Mistral Small 3 can be run privately on a single RTX 4090 or a Mac with 32GB RAM. Our evaluation was conducted on a Mac M1 Max with 64GB of RAM. Although the inference speed is not especially fast, it remains practical and acceptable given that this is a mid-sized model.
According to Mistral’s post, the model can be fine-tuned for specific domains, enabling the creation of highly accurate subject-matter experts. This capability is especially valuable in areas such as legal advice, medical diagnostics, and technical support, where deep domain knowledge is critical. It is also worth noting that, following our evaluation, several newer models have since been released, as listed below. Interested users are encouraged to test them as well.
- Mistral Small 3.1 (25.03): An updated version that added enhanced long context and state-of-the-art vision understanding capabilities.
- Mistral Small 3.2 (25.06): The version improves instruction following, reduces repetition errors, and strengthens function calling capabilities.
- Mistral Small Creative (25.12) : An experimental “Labs” model specialized for creative writing and character interaction.
The Local Advantage
Running Mistral Small 3 locally via GPTLocalhost ensures:
- Data Ownership: No cloud data leaks.
- Zero Network Latency: Faster performance on GPU and Apple Silicon.
- Offline Access: Work anywhere, including on a plane ✈️, without an internet connection.