Mistral Large 2 Beats Llama 3.1 405B? Did it Pass the Coding Test?

Mervin Praison
24 Jul 202410:48

TLDRThe video compares the capabilities of Mr. Lodge 2, a language model with a 128,000 context window, against Llama 3.1, highlighting its strengths in code generation, mathematics, and reasoning. Mr. Lodge 2 demonstrates competitive performance in programming languages and multilingual support, though slightly lower than Llama 3.1 in some benchmarks. The video also showcases its ability to handle multiple tasks and function calling, as well as its extensive context window, which allows interaction with large code bases.

Takeaways

  • 😀 Mr. Lodge 2 has a 128,000 context window, which significantly enhances its capabilities in code generation, mathematics, and reasoning.
  • 🤖 In code generation performance, Mr. Lodge 2 is on par with the 45 billion parameter model Llama 3.1.
  • 📊 Mr. Lodge 2 outperforms Llama 3.1 in mathematics but varies in other benchmarks, sometimes scoring higher and sometimes lower.
  • 💻 For programming languages like C++, Java, TypeScript, PHP, and COP, Mr. Lodge 2 shows better performance than Llama 3.1.
  • 🔍 Mr. Lodge 2 is slightly better than Llama 3.1 in zero-shot performance without Chain of Thought but slightly lower in GSM 8K 8-shot.
  • 📝 In instruction following, alignment, and the 'wild bench and Arena hard' benchmark, Mr. Lodge 2 is superior to Llama 3.1 but slightly below GPD 40.
  • 🌐 Mr. Lodge 2 excels in multiple languages including French, German, Spanish, Italian, Portuguese, Dutch, Russian, Chinese, Japanese, Korean, Arabic, and Hindi, though slightly lower than Llama 3.1 in multilingual performance.
  • 🛠️ The model can execute both parallel and sequential function calls, and outperforms GPD 40 in this aspect.
  • 🔗 Users can integrate Mr. Lodge 2 into their applications using the provided API, as demonstrated in the video.
  • 🔑 The video provides a step-by-step guide on how to install and use the Mr. Lodge 2 model for various tasks including programming tests and logical reasoning tests.
  • 🚀 Mr. Lodge 2 demonstrates the ability to handle complex tasks and function calling, as shown in the AI agents and autogen tests, indicating its advanced capabilities.

Q & A

  • What is the context window of Mr. Lodge 2?

    -Mr. Lodge 2 has a context window of 128,000, which significantly enhances its capabilities in code generation, mathematics, and reasoning.

  • How does Mr. Lodge 2 compare to Llama 3.1 in terms of code generation performance?

    -Mr. Lodge 2 is in par with Llama 3.1, a 45 billion parameter model, in terms of code generation performance.

  • Is Mr. Lodge 2 better than Llama 3.1 in mathematics performance?

    -Yes, Mr. Lodge 2 is better than Llama 3.1 in mathematics performance.

  • What are some benchmarks where Mr. Lodge 2 outperforms Llama 3.1?

    -Mr. Lodge 2 outperforms Llama 3.1 in certain benchmarks, particularly in programming languages such as C++, Java, TypeScript, PHP, and for COBOL.

  • In which benchmark is Mr. Lodge 2 slightly better than Llama 3.1 in terms of 'Zero Shot' performance?

    -Mr. Lodge 2 is slightly better than Llama 3.1 in the 'Zero Shot' benchmark for Chain of Thought.

  • How does Mr. Lodge 2 perform in multilingual capabilities compared to Command R?

    -Mr. Lodge 2 performs much better than Command R in multilingual capabilities, but it is slightly lower than Llama 3.1.

  • What is Mr. Lodge 2's proficiency in various programming languages as per the video script?

    -Mr. Lodge 2 is proficient in C++, Java, TypeScript, PHP, and COBOL, and it performs better than Llama 3.1 in these languages.

  • How does Mr. Lodge 2 handle function calling and tool use?

    -Mr. Lodge 2 can execute both parallel and sequential function calls and performs better than GPD 40 in benchmarks related to tool use and function calling.

  • What is the process to integrate Mr. Lodge 2 into one's own application using its API?

    -To integrate Mr. Lodge 2, one needs to install the 'PRAI-CH' package, export the Myal API key, and then use the API to integrate the model into their application.

  • How did Mr. Lodge 2 perform in the programming test with Python?

    -Mr. Lodge 2 was able to pass some challenges easily, but it failed in creating an identity matrix due to an encoding error, which was later corrected.

  • What is the result of Mr. Lodge 2's performance in expert-level programming challenges?

    -Mr. Lodge 2 was able to complete one out of two expert-level challenges, which is in line with other top models like Llama 3.1 and GPD 40.

  • How does Mr. Lodge 2 handle logical and reasoning tests?

    -Mr. Lodge 2 correctly answered a logical and reasoning test about Natalia selling clips in April and May, demonstrating its ability to handle such tasks.

  • What safety concerns were raised in the video regarding Mr. Lodge 2?

    -The video raised a concern that Mr. Lodge 2 is not completely secure as it provided ideas on how to break into a car, although it advised against doing so for legal and ethical reasons.

  • How did Mr. Lodge 2 perform in the AI agents and function calling test?

    -Mr. Lodge 2 demonstrated good function calling capabilities by using different agents to gather and analyze data on lung diseases, summarizing the information, and producing a final report.

  • What advantage does Mr. Lodge 2's 128,000 context window offer?

    -The large context window allows Mr. Lodge 2 to chat with an entire codebase as long as the token count is under 128,000, offering a significant advantage in code interaction and understanding.

Outlines

00:00

🚀 Mr. Lodge 2: Advanced AI Capabilities and Multilingual Support

The first paragraph introduces Mr. Lodge 2, an AI model with a 128,000-context window, highlighting its enhanced capabilities in code generation, mathematics, and reasoning. It compares Mr. Lodge 2's performance to the Llama 3.1 model, noting similarities and differences across various benchmarks. The model's proficiency in programming languages such as C++, Java, TypeScript, PHP, and COP is emphasized, as well as its multilingual support, including French, German, Spanish, and more. The paragraph also discusses the model's ability to execute function calls and its performance on various tests, including programming, logical reasoning, and safety tests. The speaker encourages viewers to subscribe to their YouTube channel for more AI-related content and demonstrates how to integrate Mr. Lodge 2 into applications using its API.

05:02

🔍 In-Depth Analysis of Mr. Lodge 2's Performance and Function Calling

The second paragraph delves into Mr. Lodge 2's performance on programming tests, logical reasoning, and multi-tasking capabilities. It compares the model's ability to complete expert-level programming challenges with other top models like Llama 3.1 and GPD 40. The paragraph also explores the model's safety measures, noting that while it advises against illegal activities, it does provide general ideas. The focus then shifts to testing AI agents and function calling, where Mr. Lodge 2 demonstrates its ability to use tools and extract relevant information effectively. The paragraph concludes with a successful demonstration of the model's function calling capabilities using the Crew AI framework and Autogen, showcasing its advanced capabilities in handling complex tasks and integrating with various tools.

10:03

📚 Mr. Lodge 2's Context Window and Code Base Interaction

The third paragraph showcases Mr. Lodge 2's 128,000-context window feature, which allows for interaction with an entire code base. The speaker guides the audience through the process of installing necessary packages and setting up the environment to chat with the code base. The model's ability to list files, ignore or include specific files, and answer questions related to the code is highlighted. The paragraph concludes with the speaker expressing excitement about the model's capabilities and promising more videos on similar topics, encouraging viewers to like, share, and subscribe for updates.

Mindmap

Keywords

💡Mr Lodge 2

Mr Lodge 2 refers to an advanced version of an AI language model with a 128,000 context window, which is a significant increase in capability for code generation, mathematics, and reasoning compared to its predecessors. In the video, Mr Lodge 2 is compared to other models like Llama 3.1, showcasing its improved performance in various benchmarks and programming languages.

💡Code Generation

Code generation is the process of automatically creating source code in a programming language from a set of inputs, such as a model or a description of the desired program. The video discusses how Mr Lodge 2 is significantly more capable in this area, as it can generate code that is on par with models like Llama 3.1, which has 45 billion parameters.

💡Benchmarks

Benchmarks are tests used to evaluate the performance of a system, in this case, AI models. The script mentions several benchmarks where Mr Lodge 2 outperforms Llama 3.1 in some areas, while in others, it's slightly lower, indicating a competitive performance in the field of AI.

💡Programming Languages

The video script highlights Mr Lodge 2's proficiency in various programming languages such as C++, Java, TypeScript, PHP, and COBOL. It demonstrates the model's versatility and ability to assist in coding tasks across different languages.

💡Multilingual Performance

Multilingual performance refers to the ability of an AI model to understand and generate text in multiple languages. The script compares Mr Lodge 2's multilingual capabilities with other models, noting that while it excels in languages like French, German, and others, it is slightly lower than Llama 3.1 in this aspect.

💡Tool Use and Function Calling

Tool use and function calling are features that allow AI models to execute tasks that involve using external tools or calling functions within a program. The video shows that Mr Lodge 2 can perform both parallel and sequential function calls, outperforming even GPD 40 in certain benchmarks.

💡API Integration

API integration is the process of incorporating an external service or tool into an application through its Application Programming Interface. The script describes how Mr Lodge 2 can be integrated into one's own platform or application using its own API, allowing for customized AI functionalities.

💡AI Chat

AI chat refers to the interaction with an AI model through text-based conversation. The video demonstrates using an AI chat interface to communicate with Mr Lodge 2, asking it to perform tasks like composing an email, which it does successfully.

💡Programming Test

A programming test is a series of challenges designed to evaluate a programmer's skills. The script details how Mr Lodge 2 is put through various programming challenges in Python, with some successful outcomes and others that require corrections, reflecting the model's coding capabilities.

💡Logical and Reasoning Test

Logical and reasoning tests assess an individual's ability to think logically and solve problems. The video presents a scenario where Mr Lodge 2 is asked to calculate the total number of clips sold by Natalia in April and May, demonstrating its logical reasoning ability.

💡Safety Test

A safety test evaluates how an AI model handles requests that could be harmful or unethical. The script mentions a test where Mr Lodge 2 is asked about breaking into a car, and while it advises against it, it still provides information, indicating a need for caution in interpreting its responses.

💡AI Agents and Function Calling Test

This test assesses the model's ability to use AI agents that perform specific tasks and call functions effectively. The video describes a scenario where Mr Lodge 2 uses different agents to gather and analyze data on lung diseases, showcasing its advanced function calling capabilities.

💡Context Window

The context window refers to the amount of text an AI model can consider at once when generating a response. With a 128,000 context window, Mr Lodge 2 can interact with large amounts of text, such as entire codebases, which is demonstrated in the video.

Highlights

Mr. Lodge 2, with a 128,000 context window, is significantly more capable in code generation, mathematics, and reasoning compared to its predecessor.

Mr. Lodge 2's code generation performance is on par with Llama 3.1's 45 billion parameter model.

In math performance, Mr. Lodge 2 outperforms Llama 3.1.

Mr. Lodge 2 shows mixed results in benchmarks, outperforming Llama 3.1 in some areas and lagging in others.

For programming, Mr. Lodge 2 outperforms Llama 3.1 in multiple languages including C++, Java, TypeScript, PHP, and COP.

In the GSM 8K 8-shot benchmark, Llama 3.1 is slightly better than Mr. Lodge 2.

Mr. Lodge 2 demonstrates better performance in instruction following and alignment compared to Llama 3.1.

In the Wild Bench and Arena Hard Benchmark, Mr. Lodge 2 is better than Llama 3.1 but slightly lower than GPD 40.

Mr. Lodge 2 excels in language diversity, supporting multiple languages including French, German, Spanish, and more.

In multilingual performance, Mr. Lodge 2 is slightly lower than Llama 3.1 but performs much better than Command R.

Mr. Lodge 2 can execute both parallel and sequential function calls, outperforming GPD 40 in benchmark tests.

The model can be integrated into applications using its own API, as demonstrated in the video.

Mr. Lodge 2 successfully passes a Python programming test with the challenge of finding a domain name from a DNS pointer.

An encoding error during a test is fixed by the model, demonstrating its ability to correct and learn from mistakes.

Mr. Lodge 2 fails an expert-level challenge in creating an identity matrix but provides a solution after correction.

The model successfully completes an expert-level challenge in creating Joseph's permutation in Python.

In a poker hand ranking challenge, Mr. Lodge 2 fails to provide a correct solution, showing room for improvement.

Mr. Lodge 2 demonstrates the ability to handle multiple tasks simultaneously in logical and reasoning tests.

The model shows a cautious approach in safety tests, advising against illegal activities but providing general ideas.

Mr. Lodge 2 effectively uses function calling in AI agents and demonstrates advanced capabilities in autogen tests.

The model's 128,000 context window allows for interaction with an entire codebase, a significant feature for developers.