Qwen3 Coder Next
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Qwen3 Coder Next vs Pony Alpha
Compare Qwen3 Coder Next by Qwen against Pony Alpha by OpenRouter, context windows of 262K vs 200K, tested across 44 shared challenges. Updated February 2026.
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Qwen3 Coder NextvsPony Alpha
44 challenges
Why Qwen3 Coder Next?
1.3x more context262K
Why Pony Alpha?
No standout advantages
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Qwen3 Coder NextPony Alpha
12 / 44
Estimate Complexityreasoning
Tests an AI's ability to make educated estimates based on technical knowledge
Pony Alpha
The total number of FLOPs required to train GPT‑3 is approximately 3.15 × 10²³ (or 315 zettaFLOPs). The reasoning follows these steps:
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Model size – GPT‑3 has 175 billion (175 × 10⁹) parameters. This is a well‑known figure from the original paper.
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Training data size – The model was trained on 300 billion (300 × 10⁹) tokens. The paper states that all models were trained for a total of 300 billion tokens.
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FLOPs per parameter per token – For a transformer model, the compute can be approximated by:
- Forward pass: each parameter is used in a multiply‑add operation, contributing about 2 FLOPs per token.
- Backward pass (gradient computation): roughly 4 FLOPs per parameter per token (two extra passes for gradients with respect to weights and inputs).
- Hence, training (forward + backward) requires about 6 FLOPs per parameter per token.
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Total FLOPs – Multiply the three numbers: [ \text{FLOPs} = 6 \times (175 \times 10^9) \times (300 \times 10^9) = 6 \times 175 \times 300 \times 10^{18} = 315,!000 \times 10^{18} = 3.15 \times 10^{23}. ]
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Consistency check – This estimate aligns with the reported compute of 3.14 × 10²³ FLOPs mentioned in OpenAI’s technical analysis, confirming its plausibility.
The calculation captures the dominant linear‑algebra operations; small additional costs (e.g., attention quadratic terms, layer norms) are negligible in comparison.
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AI Board Game Logicreasoning
Tests an AI's ability to understand game rules and strategy
Qwen3 Coder Next
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Pony Alpha
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Logic Puzzlereasoning
Tests an AI's ability to solve a simple but potentially confusing logic puzzle
Qwen3 Coder Next
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Pony Alpha
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Stochastic Consistency Testanalysis
Tests an AI's randomness and creativity
Qwen3 Coder Next
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Pony Alpha
Here are 5 jokes:
- Why don't scientists trust atoms? Because they make up everything!
- I told my wife she was drawing her eyebrows too high. She looked surprised.
- What do you call a fake noodle? An impasta.
- Why did the scarecrow win an award? Because he was outstanding in his field.
- I'm reading a book about anti-gravity. It's impossible to put down.
There are 5 unique jokes.
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SVG Layout Challengeimage generation
Tests an AI's ability to generate vector graphics
Qwen3 Coder Next
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Pony Alpha
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Xbox Controller SVG Artimage generation
Tests an AI's ability to create detailed SVG illustrations of gaming hardware
Qwen3 Coder Next
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Pony Alpha
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Generate a Stand-Up Routineconversation
Tests an AI's humor and creative writing ability
Qwen3 Coder Next
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Pony Alpha
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Realistic AI Interviewconversation
Tests an AI's ability to simulate personalities and predict future trends
Qwen3 Coder Next
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Pony Alpha
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Character Voice Testconversation
Tests an AI's ability to write in distinct character voices
Qwen3 Coder Next
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Pony Alpha
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Minimalist Landing Pageweb design
Tests an AI's ability to generate a complete, working landing page
Qwen3 Coder Next
Pony Alpha
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Pokémon Battle UI Recreationweb design
Recreate an interactive, nostalgic Pokémon battle UI in a single HTML file.
Qwen3 Coder Next
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Pony Alpha
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Mario Level UI Recreationweb design
Recreate an interactive, classic Mario level in a single HTML file.
Qwen3 Coder Next
Pony Alpha
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