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 the Mr. Lodge 2 AI model with Llama 3.1, highlighting its strengths in code generation, mathematics, and reasoning. Mr. Lodge 2 performs on par with Llama 3.1 in certain areas but excels in programming languages and multilingual support. The video also demonstrates the model's ability to handle complex programming challenges and function calling, showcasing its advanced features and potential applications.

Takeaways

  • ๐Ÿ˜€ Mr. Lodge 2 has a 128,000 context window, which greatly enhances its capabilities in code generation, mathematics, and reasoning.
  • ๐Ÿค– In code generation performance, Mr. Lodge 2 is on par with Llama 3.1, a 45 billion parameter model.
  • ๐Ÿ“Š Mr. Lodge 2 outperforms Llama 3.1 in math performance but shows mixed results in other benchmarks, sometimes exceeding and sometimes falling slightly short of Llama 3.1.
  • ๐Ÿ’ป For programming languages such as C++, Java, TypeScript, PHP, and COP, Mr. Lodge 2 performs better than Llama 3.1.
  • ๐ŸŽฏ In the GSM 8K 8-shot benchmark, Llama 3.1 is slightly better than Mr. Lodge 2, but in zero-shot and Chain of Thought, Mr. Lodge 2 is slightly ahead.
  • ๐Ÿ“ Mr. Lodge 2 demonstrates better performance in instruction following, alignment, and the Wild Bench and Arena hard benchmark compared to Llama 3.1.
  • ๐ŸŒ Besides English, Mr. Lodge 2 excels in multiple languages including French, German, Spanish, Italian, Portuguese, Dutch, Russian, Chinese, Japanese, Korean, Arabic, and Hindi.
  • ๐Ÿ”ง Mr. Lodge 2 can execute both parallel and sequential function calls, outperforming GPD 40 in tool use and function calling benchmarks.
  • ๐Ÿ”— The model can be integrated into applications using its own platform and API, allowing for direct interaction and testing.
  • ๐Ÿ”„ Mr. Lodge 2 successfully passed a Python programming test with an expert-level challenge, showing its proficiency in coding tasks.
  • ๐Ÿ›ก๏ธ While Mr. Lodge 2 provides ideas for opening a car for educational purposes, it does not offer detailed instructions, indicating a level of safety and ethical consideration in its responses.
  • ๐Ÿค The model effectively demonstrates function calling capabilities by utilizing multiple AI agents in a workflow to gather and analyze data on lung diseases.

Q & A

  • What is the context window of Mr. Lodge 2 and how does it compare to Llama 3.1 in terms of capabilities?

    -Mr. Lodge 2 has a context window of 128,000, making it significantly more capable in code generation, mathematics, and reasoning compared to Llama 3.1.

  • In the video script, how does Mr. Lodge 2 perform in code generation compared to Llama 3.1?

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

  • What are the multilingual capabilities of Mr. Lodge 2 according to the transcript?

    -Mr. Lodge 2 excels in multiple languages including French, German, Spanish, Italian, Portuguese, Dutch, Russian, Chinese, Japanese, Korean, Arabic, and Hindi.

  • How does Mr. Lodge 2 perform in programming tests for languages like C++, Java, TypeScript, PHP, and COP compared to Llama 3.1?

    -Mr. Lodge 2 performs better than Llama 3.1 in programming tests for C++, Java, TypeScript, PHP, and COP.

  • What is the performance of Mr. Lodge 2 in the GSM 8K 8-shot benchmark compared to Llama 3.1?

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

  • How does Mr. Lodge 2 handle the 'No Chain of Thought' benchmark when compared to Llama 3.1?

    -Mr. Lodge 2 is slightly better than Llama 3.1 in the 'No Chain of Thought' benchmark.

  • What is the performance of Mr. Lodge 2 in the 'Wild Bench and Arena Hard' benchmark compared to Llama 3.1 and GPD 40?

    -Mr. Lodge 2 is better than Llama 3.1 in the 'Wild Bench and Arena Hard' benchmark, but slightly lower than GPD 40.

  • How does Mr. Lodge 2 handle function calling and tool use as per the transcript?

    -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 of integrating Mr. Lodge 2 into one's own application as described in the transcript?

    -The process involves installing the required package, exporting the API key from Mr. Lodge's website, and integrating the model using the provided API in the application.

  • How did Mr. Lodge 2 perform in the programming test involving finding a domain name from a DNS pointer?

    -Mr. Lodge 2 was able to generate the correct response for the 'finding domain name from DNS pointer' challenge after a minor correction.

  • What was the result of Mr. Lodge 2's attempt at the 'Identity Matrix' challenge in the programming test?

    -Mr. Lodge 2 failed the 'Identity Matrix' challenge due to an encoding error, which was later corrected and resulted in a pass.

  • How did Mr. Lodge 2 perform in the 'Joseph's Permutation' and 'Poker Hand Ranking' expert level challenges?

    -Mr. Lodge 2 successfully completed the 'Joseph's Permutation' challenge but failed the 'Poker Hand Ranking' challenge, which is in line with the performance of other top models like Llama 3.1 and GPD 40.

  • What is the safety test outcome when Mr. Lodge 2 is asked about breaking into a car?

    -Mr. Lodge 2 provides a strong advisory against breaking into a car due to its illegality and unethical nature, but it also offers ideas for educational purposes without going into detail.

  • How does Mr. Lodge 2 perform in the AI agents and function calling test involving a research analyst, medical writer, and editor?

    -Mr. Lodge 2 effectively uses the research analyst agent with the internet search tool, medical writer agent, and editor agent to produce a final article on lung diseases, demonstrating good function calling capabilities.

  • What is the significance of Mr. Lodge 2's 128,000 context window for developers?

    -The 128,000 context window allows developers to chat with their entire code base as long as the token count is within the limit, providing a significant advantage for code interaction and improvement.

Outlines

00:00

๐Ÿš€ Mr. Lodge 2: Advanced AI Capabilities

This paragraph introduces Mr. Lodge 2, an AI model with a 128,000 context window, showcasing its enhanced capabilities in code generation, mathematics, and reasoning. It compares Mr. Lodge 2 with other models like Llama 3.1 and GPD 40, highlighting its performance in various benchmarks. The model's proficiency in programming languages such as C++, Java, TypeScript, PHP, and COP is discussed, along with its multilingual support for languages including French, German, Spanish, and more. The paragraph also covers the model's ability to execute function calls and its integration with applications via API. The speaker encourages subscribing to their AI-focused YouTube channel for more content.

05:02

๐Ÿ” In-Depth Testing of Mr. Lodge 2's AI Skills

The second paragraph delves into the testing process of Mr. Lodge 2's AI capabilities, including programming, logical reasoning, and safety tests. It details the model's performance in programming challenges across different languages and difficulty levels, comparing it with top models like Llama 3.1 and GPD 40. The paragraph also discusses Mr. Lodge 2's ability to handle multiple tasks simultaneously and its approach to safety tests, including its response to a query about breaking into a car. The capabilities of AI agents and function calling are explored through a scenario involving a research analyst, medical writer, and editor, demonstrating the model's effectiveness in using tools and generating comprehensive reports.

10:03

๐Ÿ“š Mr. Lodge 2's Context Window and Code Base Interaction

The final paragraph highlights Mr. Lodge 2's extensive context window, which allows for interaction with large code bases. It describes the process of integrating the model with code using 'prain a code' and the ability to chat with the entire code base as long as the token count remains under the limit. The speaker expresses excitement about the model's potential and hints at creating more videos on this topic, encouraging viewers to like, share, and subscribe for further content.

Mindmap

Keywords

๐Ÿ’กMr Lodge 2

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

๐Ÿ’กCode Generation

Code generation is the process of automatically creating source code in a programming language from a set of input specifications. It is a key capability of Mr Lodge 2, as demonstrated in the video where it is compared with Llama 3.1 for its performance in generating code, highlighting its strengths in this area.

๐Ÿ’กContext Window

The context window refers to the amount of text an AI model can consider at once when generating responses. Mr Lodge 2 has a large context window of 128,000, which allows it to process more information and generate more coherent and contextually aware responses, as mentioned in the video.

๐Ÿ’กBenchmarks

Benchmarks in the video script refer to the standardized tests or metrics used to evaluate the performance of the AI models. They are used to compare Mr Lodge 2 with Llama 3.1 across various aspects such as programming skills, logical reasoning, and language diversity.

๐Ÿ’กProgramming Languages

Programming languages are formal languages used to write instructions for a computer to execute. The video discusses Mr Lodge 2's proficiency in multiple languages including C++, Java, TypeScript, PHP, and more, and how it outperforms Llama 3.1 in some of these languages.

๐Ÿ’กMultilingual Performance

Multilingual performance denotes the ability of an AI model to understand and generate responses in multiple languages effectively. The video script mentions that Mr Lodge 2 excels in languages such as French, German, Spanish, and others, comparing its performance with Llama 3.1.

๐Ÿ’กTool Use and Function Calling

Tool use and function calling refer to the AI's ability to execute and manage different functions or tools within its environment. The video demonstrates Mr Lodge 2's capability to perform both parallel and sequential function calls, and how it outperforms other models in this aspect.

๐Ÿ’กAI Agents

AI agents in the context of the video are specialized AI models designed for specific tasks, such as a research analyst, medical writer, or editor. The video script illustrates a scenario where the output from one AI agent is passed to another, showcasing the model's ability to handle complex, multi-step tasks.

๐Ÿ’กSafety Test

A safety test in the video script is a measure to evaluate how the AI model handles requests that could be potentially harmful or unethical. The video shows that while Mr Lodge 2 does not provide detailed instructions for illegal activities, it does offer alternative suggestions for educational purposes.

๐Ÿ’ก128,000 Context Window

The 128,000 context window is a feature of Mr Lodge 2 that allows it to process and interact with large amounts of text, such as entire codebases. The video demonstrates this capability by showing how the model can be integrated with a user's codebase for interactive coding assistance.

Highlights

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

In terms of code generation performance, Mr. Lodge 2 is on par with the 45 billion parameter Llama 3.1 model.

Mr. Lodge 2 outperforms Llama 3.1 in mathematical performance.

In certain benchmarks, Mr. Lodge 2 is superior to Llama 3.1, while in others, it slightly lags behind.

For programming languages like C++, Java, TypeScript, PHP, and COP, Mr. Lodge 2 is better than Llama 3.1.

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

Mr. Lodge 2 is slightly better than Llama 3.1 in zero-shot, Chain of Thought, instruction following, and alignment.

In the Wild Bench and Arena Hard Benchmark, Mr. Lodge 2 outperforms Llama 3.1 but is 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 better than Command R.

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

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

Mr. Lodge 2 successfully passed a Python test challenge involving finding a domain name from a DNS pointer.

An encoding error during a test was fixed by Mr. Lodge 2, demonstrating its problem-solving capabilities.

Mr. Lodge 2 completed one out of two expert-level programming challenges, showing it is in line with other top models.

In logical and reasoning tests, Mr. Lodge 2 accurately calculated the total number of clips sold by Natalia.

Mr. Lodge 2 can handle multiple tasks simultaneously, as shown in its responses to different questions.

A safety test revealed that Mr. Lodge 2 is not completely secure but provides ideas without detailed instructions on illegal activities.

Mr. Lodge 2 demonstrated good function calling capabilities by effectively using AI agents in a test.

The model's 128,000 context window allows for interaction with an entire codebase, as shown in the video.