How to Choose the Right AI Model for Each Task

TL;DR

Choose AI models by matching capability, cost, speed, and modality to the task. Flagship models suit complex planning and difficult coding, mid-tier models handle most daily work, and smaller models fit automation and bulk processing. Open-weight options such as Kimi K3, GLM 5.2, MiniMax M3, and MiMo V2.5 Pro provide capable alternatives, although the largest require hosted access for practical use.

Transcript

This is an updated video on every AI model. You see, the AI model landscape is shifting. So, I wanted to do like a snappy little refresh to make sure that you're not missing out on some amazing new models and new use cases out there, especially with so many powerful open source AI models available now. I have personally been updating the way that I... Read More

Key Insights

• AI models are most useful when selected by workload rather than treated as interchangeable tools. The proposed categories are flagship models for maximum capability, mid-tier models for balanced daily use, light models for inexpensive automation, and specialized models for coding, media, or customization.
• Flagship models are intended for the most demanding tasks, including complex planning, brainstorming, and complicated software projects. Their increased capability can involve tradeoffs such as higher prices, slower responses, restrictions, or weaker performance in a particular modality despite strong overall results.
• GPT 5.6 Soul is presented as a flagship all-around model with Fable-level coding at half the price. Its highlighted strengths include terminal work, web-based browsing, fewer repeated permission requests, and access to image generation capabilities that Claude Fable 5 does not provide.
• Gemini 3.1 Pro is characterized as the multimodal leader because it can watch video. Its raw capability and coding performance are described as trailing other flagship models, but Google product integrations make Gemini models widely encountered through services including Gmail, NotebookLM, Google Docs, Sheets, and YouTube.
• Kimi K3 is a flagship open-weight model that can technically be downloaded and run on a local machine. The transcript says most users lack sufficiently powerful hardware, but its capability illustrates how small the performance gap between open and closed models has become.
• Mid-tier models are described as the practical choice for about 80% of everyday work because they balance capability, price, and speed. Claude Sonnet 5, GPT 5.6 Terra, and Gemini 3.6 Flash represent the established closed-source choices within this daily-driver category.
• GLM 5.2 is an open-source Chinese model described as the strongest open-weight option and as outperforming Sonnet 5 in terminal programming. Its size makes local operation impractical for most people, so a hosted version is suggested as the more accessible way to try it.
• MiniMax M3 combines near-flagship coding, a 1 million context window, and native vision capabilities. These features support screenshot-to-code tasks, user-interface automation, and multimodal agents, while its low cost makes it a favored option for powering the presenter’s Hermes agent.

Questions & Answers

Q: How should you choose an AI model for a specific task?

Choose according to the task’s required capability, acceptable price, desired speed, modality, and deployment needs. Use flagship models for the hardest planning, brainstorming, or software projects. Use mid-tier models for most routine work because they balance quality and efficiency. Smaller light models are more suitable for automation and bulk processing, while specialized models address coding, media, or customization needs.

Q: What are flagship AI models best used for?

Flagship AI models are best suited to work that demands the highest available performance, such as complex planning, intensive brainstorming, and complicated software development. The transcript places Claude Fable 5, GPT 5.6 Soul, Claude Opus 5, Gemini 3.1 Pro, Grok 4.5, and Kimi K3 in this category, while emphasizing that each has different strengths and tradeoffs.

Q: Why are mid-tier AI models useful for daily work?

Mid-tier models are useful because they combine strong capability with faster operation and more reasonable pricing than flagship options. They are described as suitable for about 80% of normal day-to-day tasks. Claude Sonnet 5, GPT 5.6 Terra, Gemini 3.6 Flash, GLM 5.2, MiniMax M3, and MiMo V2.5 Pro are presented as examples in this category.

Q: What are the main differences between Claude Fable 5 and GPT 5.6 Soul?

Claude Fable 5 is presented as the smartest model available and a strong choice for complex planning, brainstorming, and difficult software projects, but it is also described as expensive, slow, and restricted. GPT 5.6 Soul is characterized as an all-around flagship with comparable coding ability at half the price, plus strong terminal work, web browsing, and image generation access.

Q: When should Gemini 3.1 Pro be chosen over other flagship models?

Gemini 3.1 Pro is the suggested choice when video understanding or broad multimodal capability matters most, since it is described as the only frontier model that can actually watch a video. It is less attractive for direct coding use because its raw and coding capabilities are said to trail other flagships. Its extensive integration across Google products remains a major practical advantage.

Q: What makes Kimi K3 different from other flagship AI models?

Kimi K3 differs because it combines flagship-level capability with an open-weight release. Users can technically download and run it themselves, although the transcript notes that most people do not own machines powerful enough to do so. It is described as outperforming every listed model except Claude Fable 5 and GPT 5.6 Soul, showing the narrow gap between open and closed models.

Q: What are the advantages of using MiniMax M3?

MiniMax M3 offers three highlighted advantages: near-flagship coding ability, a 1 million context window, and native vision multimodality. It can accept screenshots, convert visual material into code, support user-interface automations, and power multimodal agents. The presenter also describes it as extremely cheap and reports using it successfully as a model for a Hermes agent.

Q: How can users try large open-weight AI models without expensive hardware?

Users can access large open-weight models through hosted services instead of downloading and running them locally. GLM 5.2 is specifically described as too large for most personal machines unless the user owns hardware worth hundreds of thousands of dollars. Kimi K3 presents a similar practical limitation, even though its weights can technically be downloaded and operated independently.

Summary & Key Takeaways

• AI models are divided into flagship, mid-tier, light, and specialized categories. Flagship models offer the highest performance for demanding work, while mid-tier models balance capability, price, and speed for most daily tasks. Light models target automation and bulk processing, and specialized models focus on coding, multimodality, or customization.

• The flagship group includes Claude Fable 5, GPT 5.6 Soul, Claude Opus 5, Gemini 3.1 Pro, Grok 4.5, and Kimi K3. Their strengths vary across planning, coding, browsing, image generation, video understanding, social data, reliability, openness, price, and restrictions, making task-specific selection more useful than one universal ranking.

• The mid-tier category includes Claude Sonnet 5, GPT 5.6 Terra, Gemini 3.6 Flash, GLM 5.2, MiniMax M3, and MiMo V2.5 Pro. These models are presented as practical daily drivers, with several open-weight options offering strong coding, long context, vision capabilities, or agent support at comparatively low prices.