We're very excited to announce optimized support for Mistral Large. The popular LLM is known for its flexible deployment models, multilingual support, and its strong reasoning capabilities make it a great contender for medium complexity query workloads.
Here’s a breakdown of the key improvements and enhancements:
1. Addressing Literal/Naive Instruction Following: We developed specific prompts and new agents designed to guide Mistral Large more effectively, reducing overly literal interpretations and enhancing overall query accuracy.
2. Improving Performance in Hosted Versions: Acknowledging that Mistral Large can be 2-3x slower than GPT-4o in hosted environments, we optimized token and cache usage and parallelization, significantly boosting performance and reducing latency.
3. Enhancing Reasoning Capabilities: Mistral Large reacts especially well to Chain of Thought (CoT) instructions, which improve overall reasoning effectiveness. We leveraged this by enhancing our agents to streamline complex queries and improve logical processing.
4. Handling Complex Window Functions and Nested Subqueries: To tackle challenges with writing complex window functions and nested subqueries, we implemented specialized compiler rules that address these common issues, ensuring more accurate and efficient query generation.
5. Reducing Hallucination with Columns/Tables: We focused on minimizing frequent hallucinations related to columns and tables by refining our prompt strategies and incorporating rigorous validation checks within the agents.
6. Improving Visibility into Limits and Dealing with AWS Bedrock Throttling: We added more visibility into rate limits and implemented solutions to manage AWS Bedrock throttling, ensuring smoother and more predictable performance.
We're looking forward to seeing what you will build with Mistral!