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Llm.sql – Run a 640MB LLM on SQLite, with 210MB peak RSS and 7.4 tok/s
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aldielshala
821mo ago
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Tokémon – a Pokédex for LLMs that got out of hand
by isjustintime·May 11, 2026·3 points·3 comments
AI Analysis
●●●BangerCrowd PleaserEye CandyRabbit Hole
Turning model comparison into a Pokémon-style RPG makes browsing LLMs actually fun.
Strengths
- •Gamification layer (battles, adventure mode) creates genuine engagement beyond static lists.
- •Visual stat cards and type tags make complex model specs instantly scannable.
- •Fictional 'mythical' creatures add a creative narrative hook to technical specs.
Weaknesses
- •Heavy reliance on fictional lore might distract users seeking pure technical data.
- •Long-term utility depends on keeping the 'game' mechanics fresh beyond the novelty.
Category
Target Audience
AI developers and enthusiasts tracking the model landscape
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Hugging Face · Papers With Code · LMSys Chatbot Arena
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