Update README.md

README.md

@@ -40,6 +40,59 @@ extra_gated_description: If you want to learn more about how we process your per
 This model was converted to GGUF format from [`mistralai/Mistral-Small-3.1-24B-Instruct-2503`](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503) for more details on the model.
 
+---
+Building upon Mistral Small 3 (2501), Mistral Small 3.1 (2503) adds state-of-the-art vision understanding and enhances long context capabilities up to 128k tokens without compromising text performance. 
+With 24 billion parameters, this model achieves top-tier capabilities in both text and vision tasks.
+This model is an instruction-finetuned version of: Mistral-Small-3.1-24B-Base-2503.
+
+
+Mistral Small 3.1 can be deployed locally and is exceptionally 
+"knowledge-dense," fitting within a single RTX 4090 or a 32GB RAM 
+MacBook once quantized.  
+
+
+It is ideal for:
+
+-Fast-response conversational agents.
+
+-Low-latency function calling.
+
+-Subject matter experts via fine-tuning.
+
+-Local inference for hobbyists and organizations handling sensitive data.
+
+-Programming and math reasoning.
+
+-Long document understanding.
+
+-Visual understanding.
+
+
+For enterprises requiring specialized capabilities (increased 
+context, specific modalities, domain-specific knowledge, etc.), we will 
+release commercial models beyond what Mistral AI contributes to the 
+community.
+
+Key Features
+-
+
+-Vision: Vision capabilities enable the model to analyze images and provide insights based on visual content in addition to text.
+
+-Multilingual: Supports dozens of languages,including English, French, German, Greek, Hindi, Indonesian, Italian, Japanese, Korean, Malay, Nepali, Polish, Portuguese, Romanian, Russian, Serbian, Spanish, Swedish, Turkish, Ukrainian, Vietnamese, Arabic, Bengali, Chinese, Farsi.
+
+-Agent-Centric: Offers best-in-class agentic capabilities with native function calling and JSON outputting.
+
+-Advanced Reasoning: State-of-the-art conversational and reasoning capabilities.
+
+-Apache 2.0 License: Open license allowing usage and modification for both commercial and non-commercial purposes.
+
+-Context Window: A 128k context window.
+
+-System Prompt: Maintains strong adherence and support for system prompts.
+
+-Tokenizer: Utilizes a Tekken tokenizer with a 131k vocabulary size.
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)