Which AI Should You Actually Use? Claude vs ChatGPT vs Grok vs Gemini (2026 Guide)

August 20, 2026

AI Summary

5 min read

On a recent episode of the Limitless Podcast, the hosts tackled a question that has become increasingly urgent for anyone using AI: with hundreds of models now available, which one should you actually use? The landscape has shifted from a simple choice between one or two frontier labs to a sprawling ecosystem where open-source Chinese models, enterprise-focused American labs, and niche specialists all compete. The answer, they argue, is no longer about picking the single most intelligent model—it is about matching the model to the task, the budget, and the context you have already built with it.

The Great Divide: Open Source vs. Closed Source

The hosts frame the current AI landscape around a fundamental split. On one side are the closed-source American labs—Anthropic, OpenAI, Google, and xAI (Grok). On the other are the open-source models, predominantly from China, including DeepSeek, Kimi, and GLM. The economics of this split have reversed dramatically. In June 2025, US labs generated 70% of all tokens on the routing platform OpenRouter; by the time of the episode, that share had fallen to 30%. While the value of those tokens has increased, the shift is real.

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What you'll learn

1 (00:00) **The Model Overload Problem** - The hosts introduce the core question: with 15+ models shipped in 90 days, which one should you actually use?
2 (01:17) **The Two Classes of Models: Open Source vs. Closed Source** - A clear split between Chinese open-source models and US closed-source models, with a surprising shift in market share.
3 (03:30) **The Intelligence Scorecard: Who's on Top?** - The hosts walk through the Artificial Analysis Intelligence Index, revealing the current hierarchy of model intelligence.
4 (04:41) **How the Hosts Actually Use AI** - A candid breakdown of personal usage habits, revealing a 75/25 split between Claude and other models.
5 (06:53) **The Hosts' Personal AI Stack** - A detailed look at which models each host uses for specific tasks, from coding to image generation.
6 (07:56) **Why Opus 5 Over Fable 5? The Personality Problem** - A surprising critique of the most intelligent model: Fable 5's verbose, archaic prose makes Opus 5 the better daily driver.
7 (09:20) **The Trust Issue with Chinese Models** - One host admits to a bias against using Chinese open-source models, despite their capabilities.

+ Full timestamped outline available in the app

Show Notes

We discuss the fast-changing AI model landscape and how users are increasingly choosing models based on cost, convenience, and specific tasks.

We compare major closed and open-source models, outline which tools work best for coding, writing, real-time use, and image generation, and discuss how memory and context affect enterprise and power-user workflows.

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TIMESTAMPS

0:00 Frontier Model Overload
1:09 Open Source vs Closed
3:20 Ranking Model Intelligence
5:41 Pricing Changes Everything
9:43 Cheap Models and Compute
11:14 Google and Grok Use Cases
15:30 Best Subscriptions For Most
17:41 Picking Models by Task
19:43 Agents and Knowledge Work
22:27 What Comes Next
24:50 Apple’s AI Wildcard
26:03 Final Model Recommendations

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RESOURCES

Josh: https://x.com/JoshKale

Ejaaz: https://x.com/cryptopunk7213

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Not financial or tax advice. See our investment disclosures here:
https://www.bankless.com/disclosures⁠

Josh works with Anthropic as a contractor. All views expressed are his own and do not represent Anthropic, its leadership, or its affiliates. Nothing in this episode is investment advice.