GPT vs Claude: The Fight Nobody Checked
40sThe opening hook promises a hidden truth about model comparisons, sparking curiosity and debate.
▶ Play Clip"The comparison is thorough but padded with promotional content; the title accurately represents the core topic."
This video compares OpenAI's GPT 5.6 SOL and Anthropic's Claude Opus 5, two advanced AI models released just 15 days apart. The speaker evaluates their performance in agent workflows, coding, and design tasks, revealing that the best model depends on the job. Key insights include settings to optimize Opus 5 and tips for using both models together in Agent OS.
GPT 5.6 SOL and Claude Opus 5 are compared, with the warning that benchmark comparisons are misleading because they were measured against different competitors.
GPT 5.6 comes in three tiers: SOL (top), Terra (balanced), and Luna (fast). SOL is designed for hard work like coding, agent workflows, and research.
Opus 5 has a 1M token context window and an effort dial. It is efficient by default and known for self-checking behavior.
SOL scored 80 on the Artificial Analysis Coding Agent Index, 88.8% on Work, and up to 92% with Ultra mode. It also scored 90.4% on Browse Comp and 62.6% on OS World.
Opus 5 tops Frontier Bench and GDP Val for coding. On ARC-AGI-3, it scores three times the next best model. On Zapier's Automation Bench, its pass rate is 1.5 times the next best.
OpenAI's charts were published before Opus 5 existed, so SOL was compared against Claude Fable 5, not Opus 5. Thus, a direct winner cannot be declared from those benchmarks.
In a previous test building games and a video page, SOL excelled at action and precision, while Claude was better at atmosphere and interesting details. Overall, it was a draw.
A team reported Opus 5 opened its own pages, spotted a drifted button, and fixed it before handing back the work, demonstrating valuable autonomous behavior.
SOL can write and run small programs to drive tools, using structured outputs to reduce round trips and waiting time on tool-heavy jobs.
Opus 5 coordinates sub-agents well, rarely overriding each other's work, making it strong for team-based tasks.
Do not tell Opus 5 to verify its work—it already does. Adding such instructions causes over-verification and slows it down.
Start at 'high' for quality, go down if quality holds, and go to 'max' only for important jobs to save tokens and time.
The video concludes that GPT 5.6 SOL excels at action and precision tasks, while Claude Opus 5 is better at careful, self-checking behavior and team coordination. The real winner is the combination of both models used appropriately within a platform like Agent OS.
What are the three models in the GPT 5.6 family?
SOL, Terra, and Luna.
00:46
What is the context window size of Claude Opus 5?
1 million tokens.
01:14
What score did SOL achieve on the Artificial Analysis Coding Agent Index?
80.
02:09
Why is the direct benchmark comparison between SOL and Opus 5 misleading?
Because OpenAI's charts were published before Opus 5 existed, so SOL was compared against Claude Fable 5.
02:47
What is the key difference in tool handling between SOL and Opus 5?
SOL writes and runs small programs to drive tools, while Opus 5 coordinates sub-agents.
05:06-05:21
What should you NOT tell Opus 5 to do, according to the tips?
Do not tell it to verify its work at the end; it already does that automatically.
06:03
What effort dial setting should you start with for Opus 5?
Start at 'high'.
06:18
Flawed Benchmark Comparison
Reveals that the common comparison is fundamentally flawed because the models were tested against different competitors.
02:47Opus 5's Autonomous Behavior
Demonstrates Opus 5's ability to self-correct and improve output without explicit instructions, a key advantage.
04:39Combining Both Models
Offers a practical strategy to leverage each model's strengths by assigning different roles, outperforming using either alone.
06:30[00:05] Frontier models. 15 days apart, everyone already picked a winner, but nobody checked the one thing that actually matters. The two score cards were never measuring the same fight. So, I put GPT 5.6 SOL and Claude Opus 5 side by side
[00:19] inside Agent OS. And what came out was not what I expected. I'm the digital people learn AI tools and actually use them in their day-to-day work. In this really is, where each one pulls ahead, how I run both of them inside Agent OS
[00:33] at the same time, and the one setting almost everyone gets wrong that quietly makes Opus 5 worse. That last one is near the end, so stick with me. Let's start with GPT 5.6 SOL. SOL is OpenAI's new flagship. It went generally
[00:46] available on the 9th of July. GPT 5.6 comes as a family of three. SOL sits at the top, Terra is the balanced one, Luna is the fast one. SOL is the one built for hard work, long coding jobs, agent workflows, research, computer use,
[01:00] design. It also brings two new settings. Max gives it more time to think and further and runs four agents in parallel by default, so it can split a big job and finish faster. Now, Claude Opus 5, Opus 5 landed on the 24th of July, so
[01:14] it a step change for the Opus tier. It gets close to the intelligence of their be the one you reach for every day because it works more efficiently than default. It has a 1M token context window, and it has an effort dial you
[01:29] control from low all the way up to max. The headline for me is that Opus 5 to. That's the part you feel when you're building something real. Here's how I'd use that for the AI Profit Boardroom. I'd hand Opus 5 the topics AI Profit
[01:42] Boardroom members keep asking about and let it map out a full tutorial series inside Agent OS. Outlines, hooks, lesson order, all in one pass. And that self-checking habit is exactly what a job like that needs because a gap in a
[01:54] content plan is the thing that hurts most when you spot it too late. So, these two? Soul is the tenacious one. It keeps pushing. OpenAI put it top of the artificial analysis coding agent index with a score of 80. It hit 88.8% on
[02:09] work. And with Ultra turned on, that goes up to just under 92%. It's also strong on browsing and computer use, 90.4% on Browse Comp and 62.6% on OS
[02:21] World. Opus 5 is the careful one. Anthropic put it at the top of Frontier Bench and GDP Val for coding and knowledge work. On ARC-AGI-3, model, its score is three times the next best model. On Zapier's Automation
[02:35] Bench, which tests whether a model can finish a full business task start to finish, its pass rate is around 1 and 1/2 times the next best. Now, here's the catch nobody mentions. When OpenAI published their charts, Opus
[02:47] 5 didn't exist yet. So, Soul was measured against Claude Fable 5, not theirs, they were measuring against their own models. If you line the two read a winner off them, you're comparing two different fights on two different
[03:02] charts and started building with both Inside Agent OS. And that's the reason way we did inside the AI Profit Boardroom. You can get the full zip file and we built out a complete 30-day roadmap here as use cases, so you're not
[03:18] where to plug each model in. There are daily video tutorials, the 6-week weekly coaching calls where you can share your screen and get help in real time on your own Agent OS setup. Everything about running Soul and Opus 5
[03:32] comments and description. Now, let's talk about what actually happens when you build with them. The last time we ran a full head-to-head, we tested Soul against Claude Fable 5 model. We built the same things in both, an open world
[03:44] dragon game, a dungeon crawler, a 3D racer, a Skyrim style world, a flight simulator, a neon city, and a full video page using Remotion. The pattern was clear. Soul was better at action and precision. The movement was smoother,
[03:58] the graphics were sharper, things just worked. Claude was better at atmosphere interesting. And on the video page, the Claude build was more animated and more about which model is smarter, it was about what each one is good at. Across
[04:12] call a draw. And the thing that actually decided it for me wasn't the model at it, how easy is to move around in, whether you can keep three jobs going without losing track. That's why the setup matters more than the scoreboard.
[04:26] With Opus 5, Anthropic's early access partners reported the same kind of thing on the front end. One team said the animations, games, and 3D work were the best they'd seen from an Opus model. Another said it opened its own pages in
[04:39] spotted a button that had drifted off screen, and fixed it before handing the work back. That's the behavior I care about, not the score. The fact it goes use that. I'd point Opus 5 at a landing
[04:52] Agent OS, and let it check its own layout at desktop and phone size before mobile checking behavior is the whole reason I'd give it that job for the AI Profit Boardroom instead of doing the pass myself. There's one more difference
[05:06] Soul can now write and run small programs that drive your tools for it. calling. Instead of every single tool result getting fired back through the itself and only keeps what actually matters. Fewer round trips, less
[05:21] waiting. On tool-heavy jobs, that's a real difference in speed. Opus 5 went running a team. Anthropic says it coordinates sub-agents well using a rarely has agents overriding each other's work. If you've ever had two
[05:35] agents fight over the same file inside Agent OS, you already know why that reads charts, documents, and diagrams, and it can rebuild an interface from a picture. It's strongest when you give it tools to zoom in, crop, and check itself
[05:48] as it goes. So, Soul drives the tools, Opus 5 runs the team, and both of those inside Agent OS. Now, the tips. This is the part that saves you the most time. First, that setting I promised you. On Opus 5, do not tell it to add a
[06:03] earlier models often say things like, "Verify your work at the end." or "Use a sub-agent to check." Anthropic says Opus 5 already does this on its own, and over-verify. Strip them out. Second, use the effort dial properly. Start at high.
[06:18] Go down when quality holds to save tokens and time. Go up to max only when the job really deserves it. Third, do not run two models on the same project folder at the same time. You will overwrite your own work. Give each model
[06:30] its own lane inside Agent OS. Fourth, match the model to the job. I let Soul run long autonomous builds in Agent OS, while Opus 5 handles the planning and the review pass. That combination beats either one on its own. Fifth, Opus 5
[06:44] default, and it talks you through what it's doing more as it works. So, if you front. Don't try to trim it afterwards. Sixth, if you need Opus 5 to move it at around two and a half times the normal speed. That's the one to reach
[06:59] for when you're iterating on a build and the waiting is what's slowing you down. And seventh, keep your memory system in one place inside Agent OS, so both models can read from it. That's the piece that turns them into one system
[07:11] nothing about each other. If you want the full process SOPs and 100 plus AI use cases like this one, join the AI Success Lab. Links in the comments and description. You'll get all the video notes from there, plus access to our
[07:26] community of 85,000 members who are crushing it with AI. You can get the full zip file inside the Agent OS, ready to install, and we built out a complete 30-day roadmap here as use cases. And when you go and try this yourself,
[07:40] get both models running, and then you'll hit the real questions. Which effort stepping on each other? Where to put the memory system so both models can see it? That's exactly what we work through inside the AI Profit Boardroom. You can
[07:53] get the full zip file inside the Agent OS ready to install, and we built out a complete 30-day roadmap here as use cases along with the prompts we actually coaching calls where you can share your screen and get unstuck the same day.
[08:07] this stuff right now, and you can meet them on the member map. Come and join us them on the member map. Come and join us at aiprofitboardroom.com.
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