RE: AI-Generated Summaries Container - Y003
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Mistral Small but Mighty - Apache 2.0, Multimodal & Fast
Mistral Small 3.1 is a small but mighty AI model that has been released under Apache 2.0. It has a model size of 3.1 billion parameters and is a direct competitor to Google's Gemma 3. The model has an expanded context window of 128 tokens, which is on par with Gemma 3. In terms of performance, Mistral Small 3.1 outperforms or is comparable to Gemma 3 and GPT 4 mini, with much better tokens per second.
The model is multimodal, meaning it can understand images and reason about them. It also has a low latency function calling capability, making it a great option for agentic workflows. The model is available on Hugging Face, and the weights for the model are available for both the instruct and base versions.
Key Features and Capabilities
Some of the key features and capabilities of Mistral Small 3.1 include:
📊 Multimodal capabilities: The model can understand images and reason about them.
📄 Multilingual performance: The model has strong performance in European and East Asian languages, but lags behind in Middle Eastern languages.
📈 Low latency function calling capability: The model has a low latency function calling capability, making it a great option for agentic workflows.
📊 Expanded context window: The model has an expanded context window of 128 tokens, which is on par with Gemma 3.
📈 Strong performance: The model outperforms or is comparable to Gemma 3 and GPT 4 mini in terms of performance.
System Prompt and Examples
The system prompt for Mistral Small 3.1 is available on Hugging Face, and it provides a lot of information about the model's capabilities and limitations. The prompt includes information about the model's knowledge base, which was last updated in 2023, and its ability to understand images and reason about them.
Some examples of how to get started with Mistral Small 3.1 include:
📊 Classifying an email as spam or not spam based on its content.
📸 Understanding images and reasoning about them, such as identifying objects and scenes.
📊 Transcribing images and generating structured JSON output.