Compare Claude Sonnet 4.5 by Anthropic against Qwen: Qwen3.5 27B by Qwen, context windows of 200K vs 262K, tested across 42 shared challenges. Updated February 2026.
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Tests an AI's ability to make educated estimates based on technical knowledge
To estimate the total number of Floating Point Operations (FLOPs) required to train GPT-3, we can use the standard formula for estimating compute in Transformer-based language model training. This approach relies on three key variables: the number of parameters, the number of tokens processed, and the FLOPs required per parameter per token.
Here is the step-by-step reasoning and calculation:
The most defining characteristic of GPT-3 is its scale. From the original research paper ("Language Models are Few-Shot Learners," Brown et al., 2020), the parameter count is widely known.
Training FLOPs depend heavily on the dataset size. The GPT-3 paper describes the dataset (a filtered version of CommonCrawl, WebText2, etc.) and the number of tokens processed.
To train a neural network, we perform several operations for each parameter for each token processed. The industry-standard approximation for training (as opposed to inference) includes:
Now, we plug the values into the formula:
$$ \text{Total FLOPs} = 6 \times (1.75 \times 10^{11}) \times (3.0 \times 10^{11}) $$
Multiply the coefficients: $$ 6 \times 1.75 = 10.5 $$ $$ 10.5 \times 3.0 = 31.5 $$
Multiply the exponents: $$ 10^{11} \times 10^{11} = 10^{22} $$
Combine: $$ 31.5 \times 10^{22} $$
Convert to standard scientific notation: $$ 3.15 \times 10^{23} $$
A common metric used in press releases and technical reports for GPT-3 is Petaflop-Days.
This cross-check ($3.11 \times 10^{23}$) aligns almost perfectly with our calculated estimate ($3.15 \times 10^{23}$), confirming the inputs are consistent with public records.
Based on the standard scaling law formula ($6NT$), the parameter count (175B), and the training dataset size (300B tokens):
Estimated Total Training FLOPs: $\approx 3.15 \times 10^{23}$ (Or roughly 315 Zettaflops)
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Here is the breakdown:
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Tests an AI's humor and creative writing ability
(The stage is dimly lit. A single microphone stand. The comedian walks out, adjusts the mic, takes a sip of water.)
Comedian: So, I've been doing some thinking lately. About patience. Specifically, how much of it we have left. I think we’ve officially lost the ability to wait.
We used to be okay with waiting. You could buy a magazine, you could wait for a letter. Now? If a website takes more than three seconds to load, I’m ready to call the police. I’m ready to file a restraining order against the Wi-Fi router.
I was watching a YouTube video the other day. It was a cooking tutorial. I love cooking tutorials. It’s the only time I feel like I could be a chef. But the video froze. Just froze. Right at the moment he was about to crack an egg. And I felt this physical urge to hit the screen.
I didn’t hit the screen, obviously. That’s not how it works. But I tapped the corner of the device. Hard. Like, "I am your master, do not make me wait."
And that’s the problem, right? We treat technology like a pet we’re trying to train. If the phone doesn’t open, we shake it. We tap it aggressively. We blow on the charging port. It’s like we’re trying to clear a dust bunny out of the soul of the machine.
[Paces slightly]
It’s not just the loading screens, though. It’s the silence. We can’t handle silence anymore. If you’re in an elevator with a stranger, and the music stops, you both immediately check your phones.
Why? There’s nothing to see. You’re in a metal box going up three floors. You don’t need to check your email. You don’t need to scroll through photos of your cousin’s dog. You just need to get to the second floor.
But the silence feels like an accusation. It says, "You have nothing to do." And we panic. So we scroll. We doom-scroll. We look at news about a fire in a city we’ve never visited, just so we don’t have to look at the other guy in the elevator.
[Stops pacing, looks at the mic]
I tried to fix this. I tried to go analog for a weekend. No phone, no laptop. Just me and a book.
It was terrifying. By Saturday night, I was checking my wrist for a watch I wasn’t wearing. I was looking for a notification that didn’t exist. I felt like a dog waiting for a treat that the owner forgot to give.
And the worst part? The battery anxiety. I don’t even use my phone, but I know the percentage is at 40%. And my heart rate goes up. It’s not 100%. It’s not safe. I need to plug it in.
I sat there with the charger in my hand, not plugging it in, just holding it, like a security blanket. I wasn’t using the phone. I was just using the idea of the phone.
[Pauses for effect]
I think that’s where we are. We aren't addicted to the internet. We’re addicted to the promise that something else is happening somewhere else. And the scary part is, sometimes, when I close my eyes and stop looking at the screen... nothing happens.
And I don’t know how to deal with that.
[Smiles, shrugs]
Thanks, you’ve been great. Goodnight.
(Comedian nods, walks off stage.)
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