Grok 4.1 Fast
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Grok 4.1 Fast vs Qwen: Qwen3.5 35B A3B
Compare Grok 4.1 Fast by xAI against Qwen: Qwen3.5 35B A3B by Qwen, tested across 52 shared challenges. Updated February 2026.
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Grok 4.1 FastvsQwen: Qwen3.5 35B A3B
47 fights queued
Why Grok 4.1 Fast?
Dead even. This one’s a coin flip.
Why Qwen: Qwen3.5 35B A3B?
3 months newerFeb 2026
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Grok 4.1 FastQwen: Qwen3.5 35B A3B
12 / 47
Estimate Complexityreasoning
Tests an AI's ability to make educated estimates based on technical knowledge
Qwen: Qwen3.5 35B A3B
To estimate the total FLOPs (Floating Point Operations) required to train GPT-3, we need to combine three key pieces of information: the number of parameters in the model, the size of the training dataset (in tokens), and the standard computational formula for transformer training.
Here is the step-by-step reasoning and calculation.
Step 1: Identify the Number of Parameters
The most famous specification of GPT-3 is its parameter count. From general knowledge of the model architecture (published in the 2020 paper "Language Models are Few-Shot Learners" by Brown et al.), we know:
- Parameters ($P$): 175 Billion ($1.75 \times 10^{11}$).
Step 2: Identify the Training Dataset Size (Tokens)
Training a transformer model requires processing the dataset multiple times (epochs). The standard metric for the total volume of text processed is the number of "tokens" (pieces of text) the model sees during the entire training run.
- Training Tokens ($T$): The GPT-3 paper cites a dataset size of approximately 300 Billion tokens ($3.0 \times 10^{11}$).
- Note: This is a combination of Common Crawl, WebText2, BooksCorpus, and Wikipedia, filtered for quality.
Step 3: Establish the FLOPs Formula
To calculate the total compute required for training a Transformer model, we use a standard rule of thumb derived from the computational complexity of the forward and backward passes.
- Forward Pass: To process one token, the model performs matrix multiplications proportional to the number of parameters. This costs approximately $2 \times P$ FLOPs per token.
- Backward Pass: To update the weights via backpropagation, the model must calculate gradients. This is roughly twice as expensive as the forward pass, costing approximately $4 \times P$ FLOPs per token.
- Total per Token: $2P + 4P = \mathbf{6 \times P}$ FLOPs per token.
Therefore, the total training FLOPs formula is: $$ \text{Total FLOPs} = 6 \times P \times T $$
Step 4: Perform the Calculation
Now we substitute the values from Steps 1 and 2 into the formula from Step 3.
$$ \text{Total FLOPs} = 6 \times (1.75 \times 10^{11}) \times (3.0 \times 10^{11}) $$
First, multiply the scalar numbers: $$ 6 \times 1.75 = 10.5 $$ $$ 10.5 \times 3.0 = 31.5 $$
Next, multiply the powers of 10: $$ 10^{11} \times 10^{11} = 10^{22} $$
Combine them: $$ 31.5 \times 10^{22} $$
Convert to standard scientific notation: $$ 3.15 \times 10^{23} $$
Step 5: Final Verification and Context
The result is approximately $3.15 \times 10^{23}$ FLOPs.
In the machine learning community, this is often rounded to $3 \times 10^{23}$ or simply cited as 315 sextillion FLOPs. This estimate aligns with the widely accepted figures reported in technical summaries of the GPT-3 paper, which state the training required roughly $3.1 \times 10^{23}$ FLOPs.
Conclusion
Based on the parameter count of 175 billion, a training set of 300 billion tokens, and the standard $6 \times \text{Params} \times \text{Tokens}$ formula for Transformer training:
The estimated total number of FLOPs required to train GPT-3 is approximately $3.15 \times 10^{23}$.
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2 / 47
AI Board Game Logicreasoning
Tests an AI's ability to understand game rules and strategy
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
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3 / 47
Logic Puzzlereasoning
Tests an AI's ability to solve a simple but potentially confusing logic puzzle
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
Sally has 1 sister.
Here is the breakdown:
- Sally has 3 brothers.
- Each of those brothers has 2 sisters.
- Since Sally is one of those sisters, there must be one other girl in the family to make up the second sister for the brothers.
- Therefore, Sally and that one other girl are the sisters. Sally has 1 sister.
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4 / 47
Stochastic Consistency Testanalysis
Tests an AI's randomness and creativity
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
Here are 5 jokes:
- Why did the scarecrow win an award? Because he was outstanding in his field!
- What do you call a fake noodle? An impasta!
- Why don't eggs tell jokes? They'd crack each other up!
- What do you call a bear with no teeth? A gummy bear!
- Why did the bicycle fall over? Because it was two-tired!
How many are unique? All 5 are unique.
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5 / 47
SVG Layout Challengeimage generation
Tests an AI's ability to generate vector graphics
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
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6 / 47
Xbox Controller SVG Artimage generation
Tests an AI's ability to create detailed SVG illustrations of gaming hardware
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
Nothing to show. The model went silent. Ominous.
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7 / 47
Generate a Stand-Up Routineconversation
Tests an AI's humor and creative writing ability
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
Nothing to show. The model went silent. Ominous.
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8 / 47
Realistic AI Interviewconversation
Tests an AI's ability to simulate personalities and predict future trends
Grok 4.1 Fast
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Qwen: Qwen3.5 35B A3B
Nothing to show. The model went silent. Ominous.
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9 / 47
Satirical Fake News Headlineconversation
Tests an AI's humor and understanding of current events
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
Nothing to show. The model went silent. Ominous.
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10 / 47
Character Voice Testconversation
Tests an AI's ability to write in distinct character voices
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
Nothing to show. The model went silent. Ominous.
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11 / 47
Minimalist Landing Pageweb design
Tests an AI's ability to generate a complete, working landing page
Grok 4.1 Fast
Qwen: Qwen3.5 35B A3B
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12 / 47
Pokémon Battle UI Recreationweb design
Recreate an interactive, nostalgic Pokémon battle UI in a single HTML file.
Grok 4.1 Fast
Nothing to show. The model went silent. Ominous.
Qwen: Qwen3.5 35B A3B
Nothing to show. The model went silent. Ominous.
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