GPT-4o Mini First Impressions: Fast, Cheap, & Dang Good.

MattVidPro AI
18 Jul 202416:42

TLDROpenAI has unveiled GPT-4 Mini, a cost-efficient model designed to replace GPT-3.5, offering faster and cheaper AI applications. With an 82% score on MLU, it's 60% cheaper than GPT-3.5 Turbo and supports multimodal inputs like Vision. The model is also the first to use OpenAI's new instruction hierarchy method, enhancing reliability and safety for commercial use. Despite not having cutting-edge features like GPT-4 Omni's voice mode, GPT-4 Mini is a significant step in making AI more accessible and affordable.

Takeaways

  • 🚀 OpenAI has released a new model called GPT-4 Mini, which is cost-efficient and designed to replace GPT-3.5.
  • 💡 GPT-4 Mini is intended to expand the range of AI applications by making intelligence more affordable, with a significantly lower cost compared to previous models.
  • 🏆 The model has achieved an 82% score on MLU and outperforms the original GPT-4 on chat preferences leaderboard.
  • 💰 GPT-4 Mini is priced at 15 cents per million input tokens and 60 cents per million output tokens, making it 60% cheaper than GPT-3.5 Turbo.
  • 🔍 It supports specific use cases such as handling large volumes of context quickly, which is beneficial for customer support chatbots.
  • 👀 GPT-4 Mini also supports Vision, with audio inputs and outputs expected to be added in the future.
  • 📊 The model has a context window of 128,000 tokens and handles non-English text at a cost-effective rate.
  • 📉 In terms of benchmarks, GPT-4 Mini performs well, except for Math Vista, where it scores slightly behind Gemini Flash.
  • 🔒 GPT-4 Mini is the first model to apply OpenAI's new instruction hierarchy method to improve resistance to jailbreaks and prompt injections.
  • 🔍 Updates on other features like advanced voice mode for GPT-4 Omni are expected to roll out in late July and be available to all users by fall.
  • 🔮 The video suggests that GPT-5 may not be released this year, and a public release of Sora is anticipated by the end of the year.

Q & A

  • What is the name of the new model released by OpenAI?

    -The new model released by OpenAI is called GPT 4.0 Mini.

  • What is the purpose of GPT 4.0 Mini in terms of its capabilities and intended use?

    -GPT 4.0 Mini is designed to be a cost-efficient, small model meant to replace GPT 3.5. It is intended for use cases that do not require the high level of intelligence found in GPT 4.0 Omni or GPT 4.0 Turbo, focusing on being very cheap and very fast.

  • How does GPT 4.0 Mini perform in terms of cost compared to previous models?

    -GPT 4.0 Mini is significantly more affordable than previous models, being 60% cheaper than GPT 3.5 Turbo and an order of magnitude more affordable than earlier models.

  • What is the cost per million input and output tokens for GPT 4.0 Mini?

    -GPT 4.0 Mini costs only 15 cents per million input tokens and 60 cents per million output tokens.

  • What specific use cases is GPT 4.0 Mini particularly good for?

    -GPT 4.0 Mini is particularly good for parallel multiple model calls, passing large volumes of context quickly, codebase conversation history, interacting with customer support, and it also supports Vision, with audio inputs and outputs expected in the future.

  • What is the context window size for GPT 4.0 Mini?

    -The context window size for GPT 4.0 Mini is 128,000 tokens.

  • How does GPT 4.0 Mini handle non-English text?

    -GPT 4.0 Mini handles non-English text at a more cost-effective rate, similar to the original GPT 4.0 Omni.

  • What is the significance of GPT 4.0 Mini scoring an 82% on MLU?

    -Scoring an 82% on MLU indicates that GPT 4.0 Mini is performing well and is impressive for a model of its kind, especially since it outperforms the original GPT 4 on chat preferences on the MLU leaderboard.

  • What new instruction method does GPT 4.0 Mini implement that improves its reliability?

    -GPT 4.0 Mini is the first model to apply OpenAI's new instruction hierarchy method, which helps improve the model's ability to resist jailbreaks, prompt injections, and system prompt extractions, making it more reliable for commercial applications.

  • What updates are provided regarding the release of advanced voice mode and other features of GPT 4.0 Omni?

    -Advanced voice mode is expected to be released in late July for a small group of users, with broader access by the fall. As for other features and models like GPT 5 and Sora, they are expected to be released in the future, with Sora potentially having a public release later this year.

Outlines

00:00

🚀 Introduction to GPT 40 Mini

The video discusses the release of a new AI model called GPT 40 Mini by Open AI. This model is not GPT 5, Sora, or a voice mode for Chat GPT, but a cost-efficient model meant to replace GPT 3.5. It is designed to be more affordable, aiming to expand AI applications. The model scores an 82% on mlu, outperforming the original GPT, and is priced at 15 cents per million input tokens and 60 cents per million output tokens. It is 60% cheaper than GPT 3.5 turbo and supports Vision, with audio inputs and outputs expected in the future. The model has a context window of 128,000 tokens and handles non-English text effectively. It is also the first to apply Open AI's new instruction hierarchy method, improving resistance to jailbreaks and prompt injections.

05:01

🔍 First Impressions and Testing of GPT 40 Mini

The video continues with the host's first impressions of GPT 40 Mini, noting its availability in the Chat GPT API and its potential for both free and plus users. The host tests the model's creativity by asking it to generate a connection between a pineapple and a laptop, resulting in a detailed and imaginative response. The model is also tested for its ability to handle system prompts, showing a consistent and reliable response even when prompted to act as an 'evil AI'. The host observes that the model is less censored than some other models, which could be a positive or negative depending on the user's perspective. The model's speed and flexibility are highlighted, and its ability to infer correct responses to complex questions is tested, showing impressive results.

10:04

🖼️ Multimodal Capabilities and Image Recognition

The video explores GPT 40 Mini's multimodal capabilities, specifically its ability to process images. The host uploads a photo of his channel logo and asks the model to describe it, receiving a detailed and accurate description. The model's performance is compared to that of GPT 4 Omni, with the latter providing a slightly more detailed response. The host also tests the model's ability to understand and explain the humor in a meme, noting that while the response is accurate, it lacks some of the deeper humor that GPT 4 Omni captures. The video concludes with a test of the model's ability to interpret a chart, where GPT 40 Mini provides a basic explanation but fails to recognize its own inclusion in the chart, unlike GPT 4 Omni.

15:05

🔚 Conclusion and Future Expectations

In the conclusion, the host summarizes his thoughts on the GPT 40 Mini model, praising its affordability, speed, and reliability. He expresses a desire for more cutting-edge features like those expected in GPT 5, voice mode for GPT 4 Omni, and the public release of Sora. The host also mentions the Open AI strawberry fiasco, which he plans to discuss in a future video, and hints at a potential release date for GPT 5. The video ends with a thank you to the viewers and a sign-off.

Mindmap

Keywords

💡GPT-40 Mini

GPT-40 Mini is a newly released AI model by Open AI, designed to be cost-efficient and replace GPT 3.5. It is intended for applications that do not require the high level of intelligence found in models like GPT-4 Omni or GPT-4 Turbo. The model is highlighted for its affordability and speed, aiming to make AI more accessible. In the script, it is mentioned as scoring an 82% on mlu and being 60% cheaper than GPT 3.5 Turbo, which positions it as a significant update in the AI landscape.

💡Cost Efficiency

Cost efficiency in the context of the video refers to the affordability and economic viability of the GPT-40 Mini model. The script emphasizes that this model is 'very cheap and very fast,' with pricing at only 15 cents per million input tokens and 60 cents per million output tokens. This cost efficiency is crucial for expanding the range of AI applications by making AI more affordable.

💡MLU Score

The MLU (Mean Language Understanding) score is a metric used to measure the performance of language models. In the video script, it is mentioned that GPT-40 Mini scores an 82% on MLU, indicating its strong language comprehension abilities. This score is significant as it benchmarks the model's performance against other models in the AI field.

💡Instruction Hierarchy Method

The Instruction Hierarchy Method is a new approach applied in GPT-40 Mini to enhance the model's reliability and safety. It helps the model resist jailbreaks, prompt injections, and system prompt extractions. This method is important for ensuring that the model provides safe and reliable responses in commercial applications, as highlighted in the video script.

💡Parallel Multiple Model Calls

Parallel multiple model calls refer to the ability of the AI model to handle multiple API calls or processes simultaneously. The script mentions this as one of the specific use cases where GPT-40 Mini excels, indicating its capability to process large volumes of context quickly and efficiently.

💡Vision Support

Vision support in the context of GPT-40 Mini denotes the model's ability to process and understand visual inputs, such as images. The script notes that this feature is interesting and implies that it adds to the model's versatility, although audio inputs and outputs are mentioned as upcoming features, indicating potential for further expansion in multimodal capabilities.

💡Chat GPT

Chat GPT is a platform powered by AI models that enables conversational interactions. In the video script, it is mentioned that GPT-40 Mini powers the free version of Chat GPT, suggesting that this model is integral to the platform's functionality and user experience.

💡System Prompt

A system prompt in AI refers to a set of instructions or cues that guide the model's responses. The video script tests the model's system prompt by asking it to respond as if it were an 'evil AI bent on taking over the world.' The model's responses in these tests demonstrate its ability to follow prompts and generate context-appropriate responses.

💡Image Recognition

Image recognition is the ability of an AI model to analyze and understand visual content. The script tests GPT-40 Mini's image recognition capabilities by asking it to describe a cartoon-like lemon character. The model's response shows its ability to interpret and describe visual elements, although the script notes that GPT-4 Omni provides a more detailed description.

💡Meme Understanding

Meme understanding involves the AI's ability to interpret and explain the humor or message in a meme. In the script, GPT-40 Mini is tested with a meme about project management and idea generation. The model's response shows its capability to understand and explain the humor, although it is noted that GPT-4 Omni provides a more nuanced explanation.

💡Benchmarks

Benchmarks in the context of AI models are tests or comparisons used to evaluate performance. The video script discusses benchmarks where GPT-40 Mini outperforms other models except for GPT-4. This indicates the model's competitive standing in terms of language comprehension and other capabilities.

Highlights

OpenAI has released a new model called GPT-4 Mini, which is cost-efficient and meant to replace GPT-3.5.

GPT-4 Mini powers the free version of Chat GPT and is designed for use cases that don't require the intelligence level of GPT-4 Omni or GPT-4 Turbo.

The model aims to expand the range of AI applications by making intelligence more affordable, scoring an 82% on MLU and outperforming the original GPT-4 on chat preferences.

GPT-4 Mini is priced at 15 cents per million input tokens and 60 cents per million output tokens, making it significantly cheaper than previous models.

The model is capable of handling large volumes of context quickly, making it suitable for support chat bots and processing conversation history.

GPT-4 Mini also supports Vision, with audio inputs and outputs expected to be added in the future.

The model has a context window of 128,000 tokens, which is decent for many tasks and handles non-English text at a cost-effective rate.

GPT-4 Mini is the first model to apply OpenAI's new instruction hierarchy method, improving its ability to resist jailbreaks and prompt injections.

OpenAI is planning to release advanced voice mode for GPT-4 Omni in late July, with a full rollout expected by the fall.

The release of GPT-5 is not expected this year, with a possible release window in early 2025.

Sora, another project by OpenAI, is gaining more visibility, with hopes for a public release by the end of the year.

GPT-4 Mini's image recognition capabilities are impressive, with no visible hallucinations and quick responses.

The model's response speed is lightning quick, making it a lightweight and flexible option for developers.

GPT-4 Mini's system prompt responses are reliable and not overly censored, providing a good balance for user interactions.

The model's ability to infer and respond to complex prompts, such as the bullet drop scenario, is commendable.

GPT-4 Mini's evaluation score chart shows it compares favorably to other models in many respects, despite not recognizing its own presence on the chart.

The video concludes that GPT-4 Mini is a useful model, being cheap, fast, and reliable, with a desire for more cutting-edge features from OpenAI.

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