Curious Coder
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Do join for coding resources, Handwritten notes & Quizzes! 🧑💻 Business: Curiousprogrammer12@gmail.com
Mostrar más📈 Análisis del canal de Telegram Curious Coder
El canal Curious Coder (@curious_coder) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 133 776 suscriptores, ocupando la posición 860 en la categoría Tecnologías y Aplicaciones y el puesto 1 583 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 133 776 suscriptores.
Según los últimos datos del 05 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -1 782, y en las últimas 24 horas de -74, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 5.86%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.97% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 7 844 visualizaciones. En el primer día suele acumular 2 643 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 21.
- Intereses temáticos: El contenido se centra en temas clave como iit, lpa, hyderabad, patna, internship.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Do join for coding resources, Handwritten notes & Quizzes! 🧑💻
Business: Curiousprogrammer12@gmail.com”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 06 octubre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
133 776
Suscriptores
-7424 horas
-4937 días
-1 78230 días
Archivo de publicaciones
133 776
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133 776
Repost from NeuralZone | AI Apps
🚀 GigaChat 3.5 Reasoning — a new open-source LLM that thinks before it answers.
It breaks problems into stages, builds a plan, checks intermediate results, and self-corrects. Built on GigaChat 3.5 Ultra, it explores multiple step-by-step reasoning paths for math & coding, using automated verification to reinforce correct answers.
⚡️ Proprietary linear attention makes it highly efficient on long contexts, retaining key points without re-matching from scratch. It’s also token-efficient: uses 37% fewer tokens than DeepSeek V4 Flash Preview on math problems!
📈 Benchmark gains over non-reasoning version:
• IFBench: 44 → 77
• Natural Plan: 64 → 80
• LiveCodeBench v6: 56 → 85
📦 MIT license. Weights on Hugging Face: fp8 | bf16
133 776
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