Gemini 3 Pro

Google went a different direction. Gemini 3 Pro is all about reasoning, multimodal inputs, and that million-token context window.

The benchmark numbers are wild. It hit 91.9% on GPQA Diamond. On ARC-AGI-2, the abstract reasoning benchmark, it scored 31.1% (and up to 45% in Deep Think mode). That is a huge leap over previous models. On LMArena it took the top ELO spot.

If your work is heavy on reasoning, vision, video, or you need to throw massive context at a problem, Gemini 3 Pro is built for that.

Claude Opus 4.5

Anthropic announced Opus 4.5 on November 24, 2025. They are calling it the best model in the world for coding, agents, and computer use. Bold claim.

On their internal engineering benchmarks, Opus 4.5 scored higher than any human candidate ever on their take-home exam. It also delivers higher pass rates on tests while using up to 65% fewer tokens than Sonnet 4.5. That efficiency piece matters if you are building agents that run for hours.

The pitch is clear: if you care about code, automation, and not burning through tokens, Opus 4.5 is the one.

How They Compare

Opus 4.5 is aimed at engineers building agents and writing code. It is optimized for efficiency. Gemini 3 Pro is aimed at everything else: reasoning, multimodal, long context, general purpose.

Both are frontier models. Both are available on major clouds and APIs. The honest answer is you might end up using both depending on the task.

The Real Point

The meta-point is not which model wins. The point is that two frontier models landed in the same week, both pushing hard on different axes. Reasoning, coding, agents, vision, efficiency. The pace of improvement is nuts.

If you are building with AI right now, the table is full. Pick your model, match it to your task, and start experimenting. There has never been a better time.

What excites me about Claude Opus 4.5?

While I was writing this post, a friend texted me to ask what excited me about Claude Opus 4.5. I spent a couple of hours with it today, and I would have to say… tool search.

Tool search lets Claude discover and load tools on-demand instead of pre-loading every definition at the start.

Here is how it works. You provide a catalog of tools to the API with names, descriptions, and input schemas. You mark most of them with defer_loading: true, which means they stay out of the model’s context until needed. Then you include a tool-search tool in the list. When Claude needs a new capability, it searches, finds the right tool, and only then does that tool get loaded into context.

There are two pain points this solves… expensive tokens and picking the right tool.

When you load dozens of tools upfront, the definitions alone eat up thousands of tokens. That is space you could be using for reasoning, tool outputs, and user messages. With tool search, you load only the search tool and maybe three to five relevant definitions. The overhead drops significantly.

With large libraries of tools, the model can struggle to pick the right one, especially when names or parameters are similar. The search step narrows the candidates to tools that actually match the task.

My AI Prompting Process for Generating Fantasy Football Names

Step 1: Get a ChatGPT or Claude account (or both). I love both platforms for different reasons, but the prompt techniques that I am going to explain here apply to both chat apps.

Step 2: Start a new chat. Enter this starting text: My objective is to generate a fantasy football team name. Respond OKAY if you understand the objective.

Step 3: Use one of the following prompt templates by replacing the [BRACKETED] words:

• “Generate 5 funny fantasy football team names based on [PLAYER NAME]’s name or playing style.”
• “Create 5 clever fantasy football team names inspired by the [TEAM NAME] and their history or current roster.”
• “Come up with 5 witty fantasy football team names centered around [POSITION] players.”
• “Blend NFL references with [MOVIE/TV SHOW/BOOK] to create 5 unique fantasy football team names.”
• “Generate 5 punny fantasy football team names using football terminology and common phrases.”
• “Create 5 alliterative fantasy football team names starting with the letter [LETTER].”
• “Combine [CITY/STATE] references with football terms to make 5 locally-themed fantasy team names.”
• “Generate 5 playful trash-talking fantasy football team names that imply dominating the competition.”
• “Create 5 fantasy football team names that blend [PROFESSION] terminology with football references.”
• “Come up with 5 fantasy football team names that incorporate [HOLIDAY/SEASON] themes.”
• “Generate 5 appetizing fantasy football team names that combine [FOOD] with player names or football terms.”
• “Create 5 fantasy football team names that blend [MUSIC GENRE/ARTIST] references with NFL players or teams.”
• “Combine names of [HISTORICAL ERA] figures with football terminology to create 5 unique team names.”
• “Generate 5 epic fantasy football team names inspired by [MYTHOLOGY] and NFL players or terms.”
• “Create 5 geeky fantasy football team names that combine [SCIENTIFIC FIELD/TECH COMPANY] with NFL references.”
• “Come up with 5 colorful fantasy football team names incorporating [COLOR] and player names or football terms.”
• “Generate 5 wild fantasy football team names that blend [ANIMAL SPECIES] characteristics with NFL players or terms.”
• “Create 5 electrifying fantasy football team names inspired by [WEATHER EVENT] and football references.”
• “Blend elements from [FICTIONAL WORLD/UNIVERSE] with NFL references to create 5 fantastical fantasy football team names.”
• “Generate 5 multi-sport fantasy football team names that combine NFL references with terms from [OTHER SPORT].”

Step 4: Once you find a good direction or a direction that you like, ask the AI to generate more names. You are bound to find something that you like.

Example

I loved Deadpool and Wolverine. Others might want a fantasy football team named after the blockbuster movie. I will use this prompt: Blend NFL references with Deadpool to create 5 unique fantasy football team names.

I was pleasantly pleased with Mercs with a Mouthguard, since Deadpool is known as the Merc with a Mouth in the comic books.

Let me know what you come up with and what you learned. I am always interested in learning more way to produce great results from AI models.

Bonus?

Here’s the weirdest image that I have ever created with Midjourney.