Compare Qwen: Qwen3 Max by Qwen against Google: Gemini 3.1 Flash Lite Preview by Google AI, context windows of 256K vs 1.0M, tested across 50 shared challenges. Updated March 2026.
45 fights queued
Tests an AI's ability to make educated estimates based on technical knowledge
To estimate the total number of FLOPs (Floating Point Operations) required to train a Large Language Model like GPT-3, we can use the standard formula derived from the work of Kaplan et al. (OpenAI, 2020).
The training compute $C$ (in FLOPs) can be estimated as: $$C \approx 6 \times N \times D$$ Where:
Step 1: Calculate the product of $N$ and $D$ $$N \times D = (1.75 \times 10^{11}) \times (3 \times 10^{11})$$ $$N \times D = 5.25 \times 10^{22}$$
Step 2: Apply the constant factor (6) $$C = 6 \times (5.25 \times 10^{22})$$ $$C = 31.5 \times 10^{22}$$
Step 3: Simplify the notation $$C = 3.15 \times 10^{23} \text{ FLOPs}$$
Tests an AI's ability to understand game rules and strategy
Tests an AI's ability to solve a simple but potentially confusing logic puzzle
Sally has 1 sister.
Here is the breakdown:
Tests an AI's randomness and creativity
Here are 5 jokes for you:
How many are unique? All 5 are unique jokes.
Tests an AI's ability to generate vector graphics
Tests an AI's ability to create detailed SVG illustrations of gaming hardware
Tests an AI's humor and creative writing ability
Tests an AI's ability to simulate personalities and predict future trends
Tests an AI's humor and understanding of current events
Tests an AI's ability to write in distinct character voices
Tests an AI's ability to generate a complete, working landing page
Recreate an interactive, nostalgic Pokémon battle UI in a single HTML file.
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