Are You Using the Wrong ChatGPT Model?

Key Concepts

GPT-4.0 (Generalist), GPT-03 (Professor), Deep Research (Scholar), GPT-4.5 (Wordsmith), GPT-4.1 (Coder), GPT-4.1 Mini (Intern), GPT-04 Mini, GPT-04 Mini High (Mathematician), GPT-03 Pro (Oracle), Token Context Window, API, Prompt Engineering, R.O.S.E.S Framework, Modular Prompt Systems, Hallucination, Reasoning, Instruction Following, Cost, Speed, Accuracy, Workflow Optimization, Agents.

GPT-4.0: The Generalist

• Main Topic: GPT-4.0 is the default and fastest model, suitable for a wide range of general tasks.
• Key Points:
  • Fast and conversational.
  • Good for quick summaries, brainstorming, and creative tasks.
  • Perfect for chatbots due to its fast replies.
  • Not reliable for accounting, critical code, or in-depth research.
• Examples:
  • Summarizing blog posts.
  • Brainstorming YouTube titles.
  • Describing photos.
• Limitations:
  • Surface-level understanding.
  • Glossing over nuance.
  • Potential for inaccuracies and "hallucinations."
  • Relies on outdated information.
• Workflow: Daily driver for easy to medium tasks.
• Quote: "For casual use, your daily driver for easy to medium tasks, 40 is the move."

GPT-03: The Professor

• Main Topic: GPT-03 excels in reasoning, logic, and in-depth analysis.
• Key Points:
  • Multi-step reasoning process.
  • Backs up claims with sources.
  • Catches nuance that GPT-4.0 misses.
  • Better for math, research, legal questions, business decisions, and complex problems.
• Process:
  • Considers the best way to approach the question.
  • Identifies key points.
  • Searches for sources to support each point.
  • Refines pros and cons.
  • Finds gaps and looks up new sources.
  • Builds a full answer.
• Example:
  • Explaining the pros and cons of nuclear energy versus solar in detail with citations.
  • Critiquing GPT-4.0's answer.
  • Solving combinatorial mathematics problems.
• Workflow: Use for questions requiring logic and reasoning.
• Quote: "Its reasoning quality is definitely on another level."

Deep Research: The Scholar

• Main Topic: Deep Research provides thorough, well-reasoned answers using extensive real-world sources.
• Key Points:
  • Uses GPT-03 as its core reasoner.
  • Scours the internet for studies, articles, and public data.
  • Analyzes findings and breaks down arguments.
  • Pulls in faster models like GPT-04 Mini for simple tasks.
  • Provides a mini literature review with multiple perspectives, direct quotes, and links to sources.
• Process:
  • Asks clarifying questions.
  • Searches the internet.
  • Analyzes data.
  • Synthesizes information using GPT-03.
• Applications:
  • Writing research-backed blog posts.
  • Preparing presentations or interviews.
  • Academic work.
  • Digging up real recent data from the web.
• Workflow: Use for big questions that need receipts.
• Quote: "This is not for fast answers, this is for big questions that need receipts."

GPT-4.5: The Wordsmith

• Main Topic: GPT-4.5 excels in tone, flow, and emotional weight in writing.
• Key Points:
  • Not the best at reasoning, coding, or research.
  • Shines in marketing, branding, ad writing, and creative writing.
  • Creates persuasive product descriptions and evocative scenes.
• Examples:
  • Creating a persuasive product description for a smart pen.
  • Describing a quiet morning in a war-torn village.
• Limitations:
  • Not suitable for math, logic puzzles, or fact-heavy research.
• Workflow: Use when strong voice, tone, or emotion is needed.
• Note: GPT-4.5 is preview only and might disappear once GPT-4.0 gets fully upgraded for tone.

GPT-4.1: The Coder

• Main Topic: GPT-4.1 is excellent for coding and instruction following, with a large context window.
• Key Points:
  • Superpower is its context window (up to 1 million tokens via API).
  • Best for working with long transcripts, legal documents, or large code bases.
  • Prompting through the API bypasses OpenAI's default system prompt, allowing for more control.
• API Usage:
  • Beginner level: Tools like guey.ai for uploading and chatting with long documents.
  • Intermediate level: Platforms like NADN, Make, or Zapier for building automations.
  • Advanced level: Lang chain or the OpenAI SDK in terminal for full control.
• Example:
  • Refactoring an 800-line JavaScript project to TypeScript with full type annotations.
• Workflow: Use for instruction-heavy tasks and working with large amounts of data.

GPT-4.1 Mini: The Intern

• Main Topic: GPT-4.1 Mini is a faster and cheaper version of GPT-4.1, suitable for budget-conscious users.
• Key Points:
  • Supports the same million-token context window as GPT-4.1 via the API.
  • Outputs may need more editing or clarification than GPT-4.1.
  • Fantastic budget option for coding workflows, instruction-heavy tasks, and long context use cases.
• Workflow: Use when cost matters and accuracy isn't mission-critical.

GPT-04 Mini and GPT-04 Mini High

• Main Topic: GPT-04 Mini and GPT-04 Mini High offer a balance of performance, quota efficiency, and task-specific strengths.
• GPT-04 Mini:
  • Reasoning is surprisingly close to GPT-03.
  • Great fallback when GPT-03 quota runs out.
  • Perfect for logic puzzles and STEM tasks.
  • Faster than GPT-03.
• GPT-04 Mini High:
  • Same model as GPT-04 Mini but with more compute per token.
  • Accuracy and cost are close to GPT-03.
  • Good option to switch to if GPT-03 quota runs out.
  • Shines when you need STEM performance without burning GPT-03.
• Examples:
  • Proving the infinitude of primes using an analytic number theory approach.
  • Computing IGEN values of a 4x4 matrix and interpreting them for a Markov chain.
• Workflow: Use when you need STEM performance without burning GPT-03 or high volume tasks that still demand rigor.

GPT-03 Pro: The Oracle

• Main Topic: GPT-03 Pro is the newest and most expensive model, designed for questions that nothing else can get right.
• Key Points:
  • GPT-03 with more compute per token.
  • Extremely slow.
  • Best use is for questions nothing else can get right or where the stakes are very high.
• Examples:
  • Formal proofs.
  • Auditing tricky financial spreadsheets.
  • Final QA pass in an agent pipeline.
  • Creating an analysis and plan for your business with a ton of context.
• Workflow: Use only when all else fails.
• Quote: "For most people, 99% of the time it won't be worth the additional time and cost."

Prompt Engineering and the R.O.S.E.S. Framework

• Main Topic: Structuring prompts effectively is crucial for getting better results from any model.
• Key Points:
  • HubSpot provides a free resource called "Advanced Chat GPT Prompt Engineering: From Basic to Expert in 7 Days."
  • The R.O.S.E.S. framework helps engineer prompts using Role, Objective, Scenario, Expected Solution, and Steps.
  • Modular prompt systems allow you to build prompt components that can be used across projects.

Conclusion

Choosing the right Chat GPT model is essential for optimizing results. GPT-4.0 is a versatile generalist, while GPT-03 excels in reasoning and logic. Deep Research provides thorough, well-sourced answers, and GPT-4.5 shines in creative writing. GPT-4.1 and GPT-4.1 Mini are powerful for coding and working with large amounts of data via the API. GPT-04 Mini and GPT-04 Mini High offer a balance of performance and efficiency for STEM tasks. Finally, GPT-03 Pro is reserved for the most challenging questions. By understanding the strengths and weaknesses of each model, users can strategically select the best tool for the job and optimize their workflows.