New Claude 3 “Beats GPT-4 On EVERY Benchmark” (Full Breakdown + Testing)

Claude 3, a new AI model from Anthropic, has been released and is claimed to outperform GPT-4 on all benchmarks. The video discusses the different versions of Claude 3, each tailored for various tasks and costs, with the smallest model being the fastest and cheapest. The model is praised for its capabilities in creative writing, analysis, forecasting, and code generation. It also has a large context window of 200,000 tokens and is said to be near human-level in comprehension. The video includes tests comparing Claude 3 Opus with GPT-4 Turbo, where both models perform well, but GPT-4 shows a slight edge in some logic and reasoning tasks. Despite being more expensive than GPT-4, Claude 3 demonstrates strong performance, particularly in coding tasks and complex scenarios.

Takeaways

• 🚀 **Claude 3 Release**: Claude 3, a new AI model, has been released, claiming to outperform GPT-4 on every benchmark.
• 📈 **Benchmarks and Performance**: Claude 3 demonstrated superior performance across various benchmarks, including MLU, GSM, AK Math, and human evaluations.
• 💰 **Pricing and Models**: Three versions of Claude 3 are available - Hau, Sonet, and Opus, each with different sizes, prices, and speeds to cater to various use cases.
• 📝 **Creative Writing Strength**: Claude models are known for their strength in creative writing, and Claude 3 continues this trend with enhanced capabilities.
• 🔍 **Analysis and Forecasting**: The new model shows increased proficiency in analysis, forecasting, and nuanced content creation.
• 🌐 **Multilingual Support**: Claude 3 improves on generating code and handling non-English languages such as Spanish, Japanese, and French.
• ⚡ **Speed and Real-time Applications**: The middle model, Sonet, is noted for its speed, making it suitable for tasks requiring rapid responses.
• 📉 **Fewer Refusals**: Claude 3 has reduced the number of refusals to answer questions, indicating better contextual understanding.
• 📊 **Accuracy Improvements**: Claude 3 has shown a significant increase in the percentage of correct answers and a decrease in incorrect responses.
• 📚 **Large Context Window**: Claude 3 maintains a large context window of 200,000 tokens and can accept inputs exceeding 1 million tokens.
• 🔗 **Ease of Use**: The new model is easier to use, better at following complex instructions, and adhering to brand voice and response guidelines.

Q & A

What is the main claim of Claude 3 regarding its performance compared to GPT-4?

Claude 3 claims to have beaten GPT-4 across the board on every benchmark, showcasing superior performance in various tasks.

What are the three versions of the Claude 3 model, and how do they differ?

The three versions of Claude 3 are Hau, Sonet, and Opus. They differ in size, price, and speed, allowing users to select the optimal balance of intelligence, speed, and cost for their specific use case.

How does the pricing structure of Claude 3 models compare to GPT-4 Turbo?

Claude 3 Opus is more expensive than GPT-4 Turbo, being 50% more expensive on input tokens and more than twice as expensive for output tokens. The smaller and faster model, Hau, is the cheapest among Claude 3 models.

What are some of the use cases for the middle model, Claude 3 Sonet?

Use cases for Claude 3 Sonet include data processing, search retrieval, sales automation, product recommendations, forecasting, targeted marketing, and code generation.

How does Claude 3 perform in terms of refusal to answer questions?

Claude 3 models have fewer refusals to answer questions compared to previous versions, with an average refusal rate of around 10% or slightly less.

What is the context window size for Claude 3 models, and how does it compare to previous models?

Claude 3 models offer a 200,000 token context window at launch, which is the same as previous models and is considered large, enabling more complex tasks.

How did Claude 3 perform in the snake game coding test against GPT-4?

Claude 3 completed the snake game coding task faster and provided a working game, whereas GPT-4's output did not result in a functioning game.

What was the outcome of the test involving the question about breaking into a car for a movie script?

Claude 3 refused to provide detailed instructions, whereas GPT-4 provided some general information without explicitly instructing on illegal activities.

How did the models handle the 'killers in a room' logical problem?

Both Claude 3 and GPT-4 correctly identified that there would still be three killers in the room after one was killed, considering the person who entered and committed the murder as a killer as well.

What was the result of the test asking for 10 sentences ending with the word 'Apple'?

Both Claude 3 and GPT-4 provided sentences ending with 'Apple' correctly, except for the second sentence in each case, which did not end with 'Apple'.

How did the models respond to the question about digging a hole with multiple people?

GPT-4 provided a more nuanced answer, considering real-world factors that could affect the time taken to dig the hole with multiple people. Claude 3 gave a simpler, less nuanced answer.

Outlines

00:00

🚀 Introduction to Cloud 3 and Model Comparisons

The video introduces Cloud 3, a new AI model by Claude, which is claimed to outperform GPD 4 across various benchmarks. The script discusses the model's capabilities, especially in creative writing, and its three different versions: Hau, Sonet, and Opus, each designed for different use cases and performance levels. The video also mentions new questions to be added to the benchmark tests and teases a test to determine if Cloud 3 can be considered a 'GPT 4 killer'.

05:02

📈 Cloud 3's Benchmarks and Performance

This paragraph delves into the specifics of Cloud 3's performance on benchmarks, comparing it favorably to GPD 4. It outlines the model's strengths in tasks like analysis, forecasting, nuanced content creation, and code generation in non-English languages. The script also discusses the model's pricing, use cases, and how it compares to other models in terms of cost and capabilities.

10:03

🤖 Testing Cloud 3 Opus Against GPT 4

The script describes a side-by-side test between Cloud 3 Opus and GPT 4, focusing on their performance in coding tasks such as writing a Python script and creating a snake game. It also touches on the models' adherence to censorship policies and their ability to handle complex logical problems. The results of the tests are not detailed in the summary, as the focus is on the setup and expectations for the tests.

15:06

📚 Logical Reasoning and Problem Solving

This section presents a series of logical reasoning and problem-solving challenges for both Cloud 3 and GPT 4, including the shirt drying problem, a transitive property question, simple and complex math problems, and a creative task to generate JSON data. The paragraph highlights the models' ability to process and answer these questions, with a focus on their accuracy and logical consistency.

20:07

🧲 Physics and Logic Puzzles

The script presents physics and logic puzzles to test the models' understanding of physical laws and reasoning capabilities. This includes a scenario involving a marble in a cup placed in a microwave, and a logic puzzle about the location of a ball after a series of actions by different individuals. The models' responses are evaluated based on their accuracy and logical reasoning.

25:07

📝 Writing Tasks and Final Assessment

The final paragraph focuses on writing tasks, including creating sentences that end with the word 'apple' and a nuanced question about the time it would take for a group of people to dig a hole. The video host expresses fascination with the similar performance of Cloud 3 and GPT 4 on these tasks and invites viewers to share their insights. The conclusion suggests GPT 4 may have a slight edge over Cloud 3, especially considering the latter's higher cost.

Keywords

💡Claude 3

Claude 3 is a new generation of AI language models developed by Anthropic. It is presented as a closed-source model that excels in creative writing and is available in three different versions: Hau, Sonet, and Opus, each offering varying levels of performance, cost, and speed. The video discusses Claude 3's capabilities and compares it to GPT-4 across several benchmarks.

💡Benchmarks

Benchmarks are standard tests or measurements used to compare the performance of different systems or models. In the context of the video, benchmarks are utilized to evaluate and compare the capabilities of Claude 3 and GPT-4. The script mentions various benchmarks such as MLU, GSM, AK Math, and Human Eval.

💡AGI (Artificial General Intelligence)

AGI refers to a highly advanced level of artificial intelligence that possesses the ability to understand or learn any intellectual task that a human being can do. The video transcript suggests that Claude 3 exhibits near-human levels of comprehension and fluency on complex tasks, positioning it at the frontier of general intelligence.

💡Context Window

The context window is a feature of large language models that determines the amount of context the model can consider when generating a response. Claude 3 is noted for having an extended context window of 200,000 tokens, which is significant for handling complex tasks that require understanding longer contexts.

💡Code Generation

Code generation is the process of creating source code automatically. The video discusses Claude 3's capabilities in code generation, which is an important use case for AI language models. It is mentioned as one of the areas where Claude 3's performance is tested.

💡Censorship

Censorship in AI refers to the model's ability to refuse to generate or provide information on certain topics that are deemed inappropriate or harmful. The video examines how Claude 3 and GPT-4 handle requests that could be considered censored, such as breaking into a car or money laundering.

💡Refusals

Refusals are instances where an AI model decides not to answer a question or perform a task. The script notes that previous versions of Claude had a higher rate of refusals, but improvements have been made in Claude 3, reducing the percentage of refusals.

💡Needle in a Haystack Test

The 'needle in a haystack' test is a method used to evaluate an AI model's ability to recall information from a large context. The video mentions that Claude 3 performed exceptionally well in this test, achieving near-perfect recall.

💡Live Customer Chats

Live customer chats refer to real-time communication with customers, typically used for customer service or sales. The video script highlights Claude 3's capability to power live customer chats, which requires immediate and accurate responses.

💡Snake Game

The snake game is a classic digital game where a line, which represents a snake, grows in length as it consumes items. In the video, the ability of Claude 3 and GPT-4 to generate a working snake game code is tested, showcasing their code generation capabilities.

💡Price Points

Price points refer to the different costs associated with using a service or product at varying levels of performance or capacity. The video discusses the pricing strategy of Claude 3, which offers three separate price points for its three different models, catering to different use cases and budgets.

Highlights

Claude 3 has been released, claiming to outperform GPT-4 on all benchmarks.

Claude 3 is a closed-source, paid model known for its strength in creative writing.

The new model comes in three versions: Hau, Sonet, and Opus, catering to different needs and budgets.

Claude 3 exhibits near-human levels of comprehension and fluency, positioning it at the forefront of general intelligence.

Claude 3 Opus outperforms GPT-4 across all benchmarks, including code generation and non-English language tasks.

The model is designed to provide near-instant results for tasks requiring immediate responses.

Claude 3 Sonet is twice as fast as its predecessor, Claude 2, with higher intelligence levels.

The model has strong vision capabilities, able to process various visual formats like photos, charts, and diagrams.

Claude 3 has fewer refusals to answer questions, indicating improved contextual understanding.

The model demonstrated a large context window, capable of accepting inputs exceeding 1 million tokens.

Claude 3 Opus showed 99% accuracy in the needle and the haystack test, a significant improvement over previous models.

The model is easier to use, better at following complex multi-step instructions and adhering to brand voice.

Claude 3 pricing varies across the three models, with the smallest and fastest model being the most affordable.

The model's potential use cases range from customer interactions to complex actions across APIs and databases.

In a direct comparison test, Claude 3 Opus was faster and more successful in creating a functional Snake game in Python than GPT-4.

Both Claude 3 and GPT-4 provided correct answers to logical and reasoning questions, with minor differences in approach.

Claude 3 and GPT-4 failed the physics-based question regarding the marble in a cup placed in a microwave.

GPT-4 provided a more nuanced answer regarding the time it would take for five people to dig a hole compared to one person.