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HTML

Build an interactive neural-net explainer

the prompt
Build a single self-contained HTML page that teaches a beginner how a small neural network learns. It must be a genuinely interactive explainer, not a static diagram. Requirements: a visual diagram of a tiny feed-forward network (input → hidden → output) with neurons and weighted connections; a "Train" button that runs gradient descent on a simple task (e.g. learning XOR or fitting a curve) and animates the network learning; a live loss curve that updates as training progresses and visibly trends down; a control to change the learning rate and a "Reset" button; and clear, friendly labels so a first-time learner understands what they're seeing. Design matters most here — the spacing, alignment, color, and overall polish should look like a professional educational product, not an AI-generated page. Make it beautiful and genuinely useful for someone learning machine learning 101. All CSS in a `<style>` tag and all JS in a `<script>` tag — no external libraries, images, or fonts. Return ONLY a single complete self-contained HTML file, no markdown fences, no explanation.
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JAN '25
JUNE '26
All 11 models · same prompt · $2.58 total
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SIMMONS'S PICK
Opus 4.8
$1.45
GPT-5.5
$0.42
Gemini 3.5
$0.03
Grok 4.3
$0.30
GLM 5.2
OPEN
$0.26
Qwen 3.7
OPEN
$0.02
DeepSeek V4
OPEN
$0.01
Mistral Large
OPEN
$0.04
Kimi K2.7
OPEN
$0.02
MiniMax M3
OPEN
$0.01
GPT-OSS 120b
OPEN
$0.01